JP2001084288A - Method for deciding input parameter of optical simulation, method for transferring image data and computer-readable recording medium with their programs recorded thereon - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an input parameter deciding method capable of easily providing a reflection model type parameter value to be input value as a physically grounded value in a short time, when performing optical simulation using a CG. SOLUTION: Angle distribution data (i2) of spectral reflectance of each of sample which are measured respectively about at least three samples, each of which has only one different condition about a plurality of conditions including hue, saturation, lightness and surface state are converted into RGB coordinate systems on the basis of reference light (s1 and s2). A reflection model expression (i1) is fit to them due to a regression analysis to calculate the optimum values of parameters respectively (s3), and parameter dependence information, representing the correspondence relation between the samples and the parameter values, is generated. Then, the optimum values of parameters about the objects are calculated, on the basis of data (i11 and i12) about the hues and surface states of the simulation objects and the parameter dependency information (s16).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION The present invention relates to an optical simulation program as a pre-process for simulating a coloring state of an object under a predetermined light source using a reflection model formula having a predetermined parameter. An input parameter determination program for an optical simulation for determining the above parameter values, which is input data of the program, and an image data of an arbitrary object created on a computer on the sender side including the input parameter determination program on the sender side. The present invention relates to an image data transmission program for accurately displaying an image on an output device.

[0002]

2. Description of the Related Art In recent years, optical simulation programs using computer graphics (hereinafter referred to as CG) have
It has been widely used in the field of lighting, the imaging industry, and the fields of architecture and civil engineering. By using an optical simulation program, for example, how the building is illuminated when the lights are turned on at night,
It is possible to simulate how the image looks to the human eye, and check the result by color-outputting it to a display or printer. The most basic algorithm used in such an optical simulation program is a ray tracing method. this is,
It tracks the trajectory of light that repeats reflection and refraction in each direction, and determines the brightness of each surface of the object viewed from the observer. When performing these optical calculations, we assume a reflection model (a physically based model and a model that simply looks like it) that represents the characteristics of reflection, and have a spectrum for each wavelength. The mainstream method is to calculate the three types of light of RGB based on the rule of additive color mixing and to superimpose the light (three-band method). When performing an optical simulation by such a method, data on the reflectance of the material surface and the light distribution of the light source are indispensable.

Here, data relating to the light distribution of the light source,
That is, the light distribution data of the lighting equipment is held by each lighting manufacturer, and an environment in which the user can use the data is established. However, regarding the data on the reflectivity of the material surface, the actual measurement data is hardly available due to the fact that instruments for measuring the reflectivity distribution in each direction of the material are very expensive and not widely used. It is. For this reason, an optical simulation program using CG that has been on the market up to now has:
The reflectivity values of the materials used among them were not standardized by the respective manufacturers, and the form of the reflection model used for approximation was various. Therefore, when using the above-mentioned optical simulation programs, not only in the imaging industry but also in construction, civil engineering, and even lighting manufacturers, for the reflectance of materials, use the reference values given by the software manufacturers, Enter the empirical values and temporary values, perform the calculation for the time being, judge the result as the evaluation criterion based on the experience of the expert and the quality of the appearance, and repeat the process until the good output result is obtained while correcting the reflectance value. This was always performed (the above is referred to as a first conventional technique).

[0004] However, in such a trial-and-error simulation method, since there is no fixed standard, the obtained result is always ambiguous due to the intent of the maker and the like, and an advanced algorithm is used. Nevertheless, there was a high risk that the results would be far from reality. For example, in an optical simulation program, materials are roughly classified into plastic, metal, etc., and a few reflection models are prepared. However, when an actual simulation is performed, the target material is clearly included in this classification. Users often have no idea if this is true. In such a case, the user often makes a judgment based on the result of appearance. In addition, since the standard of the input value of the reflectance and the reflection model formula in each simulation program on the market are different, the input value which is the assumption of the simulation is made public to a third party for comparison and examination. It is also a problem that the conditions for conducting cooperative activities and competitions between various groups are not established, which hinders technical development. In addition, in the above-mentioned method, since the user needs to judge the result and change the input value, the user spends more time in the simulation than the calculation time by the computer. Not only the processing time becomes longer, but also a huge amount of manpower is required. Therefore, it has been a problem to find a method of inputting the reflectance that has a certain standard and has a physically basis without mixing the intention of the maker, and to shorten the processing time.

[0005] An optical simulation method (referred to as a second prior art) described in Japanese Patent Application Laid-Open No. 10-247256, for example, can partially solve such a problem. In this method, a database is prepared in which the measured data of the reflectance of each material is directly input, and the spectrum of the light is also input as it is (the multi-band method is used instead of the three-band method) to perform the calculation. . This is an ideal method in the sense that, unlike the trial and error method as in the first conventional technique, human intention and ambiguity are not mixed in the result.

Further, in 1996, as a method using one of the three-band methods (equivalent object color conversion method), a method of calculating the reflectance of a material in consideration of the color of a light source (the third conventional technology). Is published (Hideki Tajima, "Study on color reproduction method by CG under low pressure sodium lamp illumination", Journal of the Illuminating Engineering Institute, Vol. 80, No. 8A, 1996). This method is
As a pre-process of the lighting calculation simulation, RGB of the object color is obtained from the spectral distribution of the light source and the spectral characteristics of the object, and the RGB values are input as color information data variables of the lighting calculation simulation program. The RGB input obtained with the spectral distribution kept constant is input.

[0007]

However, the second and third prior arts have the following problems. First, in the above second prior art, it is necessary to input and store all the actual measured data of the reflectance of all the materials that can be simulated, and it takes an enormous amount of calculation time. There was a point. At present, simulations using this method can be managed in some areas where the types of materials used are small and under the limited conditions that a computer with the highest level of performance can be used. It is just that. In particular, in fields such as the construction and civil engineering fields where a huge variety of materials need to be considered, it is at least not possible at present to perform such a simulation.

[0008] In the third prior art, 3
Since a type of band method is used, and there is no need to measure and store a large amount of reflectance data of the sample, it can be said that this method is much more practical than the second conventional technique.
However, in the third prior art, only the diffuse reflection is considered as the reflection characteristic of the material, and the specular reflection which is one of the important components of the reflection characteristic is not considered. Therefore, if a material having specular reflection characteristics is used, an accurate simulation result cannot be obtained.
Or, for this part, trial and error processing similar to that of the first prior art is required, and problems remain in terms of simulation accuracy and processing time.

The present invention has been made in view of such circumstances, and does not require a high-performance computer, expensive measuring equipment, or special experience of an operator, and is easy and quick for anyone. It is a first object of the present invention to obtain an optimal parameter value having a valid basis, and to enable high-precision optical simulation using the parameter value.

In recent years, e-commerce using the Internet and the like has been rapidly spreading, and documents, drawings, designs, and the like for meetings have already been transferred from the order receiving side to the order receiving side through the network. It is actively exchanged from the side to the order receiving side. In electronic commerce and simple business meetings as described above, information must be accurately transmitted from the sender to the receiver. Otherwise, if a meeting in the manufacturing industry is taken as an example, complaints will occur frequently after delivery or during production due to discrepancies in information recognition between the ordering side and the ordering side. Of the documents, drawings, drawings representing designs, etc. exchanged here, for documents and drawings,
From a technical perspective, it can be said that there is little difficulty in transmitting information. However, it is very difficult to accurately transmit a picture expressing a design, that is, image data (image data). This is due to the following two problems. A: The same image data does not look the same on different computers. B: It is difficult to transfer the color specified by the designer to the computer in a correct manner and reproduce it on the computer.

Here, the above problem B is basically the same as the first problem described above. Therefore, the problem B can be solved by achieving the first object. On the other hand, as for the problem A, as a solution to this problem not on a local network but on a network, there is ColorSync developed by Apple Computer, Inc. (h
ttp: //www.apple.co.jp/colorsync/). This is software that has the function of correcting each computer on the network and performing color matching, and is currently applicable to computers manufactured by the company and peripheral devices of its cooperating companies. Also, by late 2000,
It will be available on third-party computers. However, the image data (image data) cannot be accurately transmitted from the sender to the receiver only by solving one of the problems A and B. That is, if only the above-mentioned problem (A) is solved, only color matching on the net is performed, and colors in the real world (colors that can be concretely expressed by industrial standards used other than computers) will be used. Since the colors of the virtual world (the world of virtual reality such as RGB, the color of the world on the Internet) are not associated, the real colors cannot be transmitted to a third party. Also, if only the above-mentioned problem (B) is solved only, colors can be reproduced only on the same computer, so in the Internet society, correct colors are communicated to third parties located far away from each other to communicate. It is not possible. Accordingly, a second object of the present invention is to solve the above problem B by achieving the above first object, and also to solve the above problem A, so that image data (image data) is sent from the sender to the receiver. Data) can be conveyed accurately.

[0012]

In order to achieve the first object, a first invention simulates a color development state of an object under a predetermined light source by using a reflection model formula having a predetermined parameter. In the method of determining input parameters of the optical simulation for determining the parameter values of the object, at least three samples that differ from each other only in one of a plurality of conditions including hue, saturation, lightness, and surface state. The spectral reflectance data conversion step of converting the measured angular distribution data of the spectral reflectance of each sample into a predetermined coordinate system related to the coloration of the material based on the reference light, and the spectral reflectance data conversion step. The regression analysis was used to fit each of the above reflection model equations to the data of the specified coordinate system for the coloration of the material for each sample. A parameter dependency information generating step of generating parameter dependency information indicating a correspondence between the sample and the parameter value, and obtaining a color and a color of the surface of the input object. A parameter value calculating step of calculating a value of the parameter relating to the object based on the data relating to the surface state and the parameter dependency information obtained in the parameter dependency information generating step. It is configured as a method for determining an input parameter of an optical simulation. Further, the method further comprises a relational expression obtaining step for obtaining a relation between data relating to color under a certain light source and a parameter relating to the color constituting the parameter, and in the parameter value calculating step, the input color of the surface of the object Can be converted into data relating to color under a certain light source, and further into parameters relating to color based on the relational expression obtained in the relational expression obtaining step. In the parameter value calculating step, when converting the input data relating to the color of the surface of the object into data relating to the color under a certain light source, the characteristic data of the predetermined light source used in the optical simulation is converted. It is desirable to selectively use the case where the object is provided on the reflectance side and the case where the object is provided on the light source side. When the characteristic data of the predetermined light source used in the optical simulation is provided on the reflectance side of the object, a calculation is performed based on the characteristic data of the predetermined light source and the reflectance data of the surface of the object. When the characteristic data of the predetermined light source used in the optical simulation is provided on the light source side, the calculation is performed based on the characteristic data of the reference light and the reflectance data of the surface of the object. Here, as a method of dividing the cases, for example, 1
If the target is a kind of light source, the characteristic data of the light source is provided on the reflectance side of the target object. If the target is a plurality of light sources of different colors in the optical simulation, It is conceivable to perform a process of giving the characteristic data of the light source to the light source side. Furthermore,
In the parameter-dependent information generation step, a predetermined value expressing the degree of fitting obtained by the fitting of the reflection model formula (for example, a standard error of an estimated value if the fitting is based on the least squares method) is output. By doing so, the reflection model equation can be used to determine how close the actual reflectance value can be. Thus, for example, it is possible to input a plurality of available reflection model equations, compare the output values, and select the most appropriate reflection model equation.

Further, in order to achieve the second object,
According to a second aspect of the present invention, there is provided an image data transmitting method for accurately displaying image data of an arbitrary object created on a computer on a sender side on an output device on a receiver side. Prior to a series of steps related to the input parameter determination method described in the above, a sender-side correction information data creating step of creating sender-side correction information data including environmental information on the indoor and output devices on the sender side;
Image data can be obtained by using any image creating means based on the sender-side correction information data obtained in the sender-side correction information data creation step and the parameter values obtained by a series of steps related to the input parameter determination method. After the creation, the sender-side correction information data integration step of attaching or embedding the sender-side correction information data obtained in the sender-side correction information data creation step to the image data; A receiver-side correction information data creating step for creating receiver-side correction information data consisting of environmental information relating to the output device; and the image data obtained in the sender-side correction information data integration step, wherein the image data obtained in the sender-side correction information data integration step is obtained by an arbitrary method. After being handed over to the recipient
Based on the sender-side correction information data attached or embedded in the image data and the receiver-side correction information data obtained in the receiver-side correction information data creation step,
An image data correcting step of correcting the image data. Further, if a color value obtained by a series of steps related to the above input parameter determination method is out of a range that can be expressed by an output device on a sender side or a receiver side, a warning output is performed, so that a user can perform the warning output. It is possible to always be aware of the output limit of the output device and to handle extremely accurate image data.

If the color value obtained by the series of steps relating to the input parameter determination method is out of the range that can be expressed by the output device on the sender side, the color value is expressed by the output device. Approximate with the possible range of values,
The information of the approximated color value is transmitted from the sender side to the receiver side, or the image data corrected in the image data correction step is displayed on an output device of the receiver side, and optionally. By outputting the actual color information on the color at the designated position, the receiver can obtain not only an image but also extremely specific image information. When the design is used as a criterion for decision making in electronic commerce or the like, it is extremely effective to be able to transmit such specific image information. The arbitrary image creating means for creating image data includes, for example, an optical simulation that accurately simulates the reflection of a light source and an object and faithfully reproduces the color of the object under the light source and environment. 3 possible
It is compatible with either two-dimensional computer graphics software or two-dimensional or three-dimensional computer graphics software that displays the target color specified by the user without performing the simulation. Furthermore, in each of the above steps, if a setting / input request screen prompting the user for various settings or input is sequentially output, even a novice user who has no knowledge of color engineering or image processing engineering can easily operate. Is possible. All of the above methods can be converted into computer programs.
-Provided to a user in a state of being stored in a storage medium such as a ROM or via a network such as the Internet.

[0015]

Embodiments of the present invention will be described below with reference to the accompanying drawings to provide an understanding of the present invention.
It should be noted that the following embodiments are examples embodying the present invention, and do not limit the technical scope of the present invention. FIG. 1 is a flowchart showing a processing procedure of an input parameter determination program according to the first embodiment of the present invention. FIG. 2 is a block diagram showing a schematic configuration of an input parameter determination device Z1 equipped with the input parameter determination program. FIG. 3 shows an example of measured data of the angular distribution of the spectral reflectance, FIG. 4 shows an example of the relationship between the specular gloss of the sample and the optimal (a ₄ , a ₅ ), and FIG. 5 shows the calculated spectral data of the sample Sample1. FIG. 6 is a graph showing the wavelength dependence of the reflectance, and FIG. 6 is a reflection model equation (solid line) predicted according to the first embodiment of the present invention.
7 is a reflectance distribution diagram comparing the measured data (points) with the measured data. FIG. 7 shows that the input parameter determination program according to the first embodiment is used as a preprocess, and an illumination simulation program is used to perform an illumination simulation calculation using a ray tracing method. Result image (parameters of surface condition in four rows were changed in 4 steps), actual site photos,
FIG. 8 shows a straight line AB on a high column in each image shown in FIG.
FIG. 6 is a diagram showing a profile of brightness of image data in FIG. FIG. 9 is a flow block diagram showing a flow of processing in an image data transmission program according to Embodiment 2 of the present invention, and FIG.
Examples of UI, FIGS. 11 to 17 show indoor environment settings,
Gamma correction value setting, white point setting, three primary color value setting,
FIG. 18 shows an example of a dialog box for inputting a light source type, a surface state, and an object color, FIG. 18 shows an example of a dialog box for performing various outputs relating to colors, FIG. 19 is an explanatory diagram of image conversion in the image data transmission program, and FIG. FIG. 21 shows the chromaticity coordinates of the Munsell color used in the specific example of the second embodiment.
23 shows a CG shape produced by two-dimensional CG software in the specific example of the second embodiment, FIG. 22 shows a CG shape produced by three-dimensional CG software in the specific example of the second embodiment, and FIG.
FIG. 24 is a diagram showing a saturated region in the specific example of the second embodiment, and FIG.
FIG. 25 is a measurement result when only the color matching on the net is used without using the present invention (the above-described image data transmission program), and FIG. 26 is a time required to create a CG of the specific example of the second embodiment. It is.

(Embodiment 1) An input parameter determination apparatus Z1 according to Embodiment 1 is composed of, for example, a computer such as a personal computer or a workstation, and an input parameter determination program that operates on the computer. An existing lighting simulation program is installed on the computer together with the input parameter determination program. The illumination simulation program simulates a color development state of an object under a predetermined light source by using a reflection model equation having a predetermined parameter. The input parameter determination program executes the simulation by the illumination simulation program. Prior to this, the parameters of the reflection model formula as input data of the illumination simulation program are determined. here,
The input parameter determination program may be an independent program separate from the lighting simulation program, or may be incorporated as a pre-processing routine in the lighting simulation program, but will be described as an independent program in the first embodiment. . The input parameter determination program is, for example, a CD-RO
It is provided to the user in a form recorded on a recording medium such as M or via a network such as the Internet.

FIG. 2 shows the input parameter determining device Z1.
FIG. Input means 1, such as a keyboard and a mouse, CPU2, RAM3, display device 4, such as a CRT display, and storage means 5, 6, such as a hard disk.
7 and 8 are connected via a bus line 9. The storage means 5 stores the module of the input parameter determination program together with the module of the illumination simulation program. The storage means 6 stores input data such as a reflection model formula used in the illumination simulation program and information on a color to be simulated, and the storage means 7 stores measured data of a sample described later, and the storage means 8. Stores parameter dependency data and various work files, which will be described later.

Next, the operation of the input parameter determination device Z1, that is, the processing procedure of the input parameter determination program will be described with reference to the flowchart shown in FIG. Here, for example, it is assumed that a series of materials having the same quality, such as injection-molded plastic and paint, are treated as simulation targets. Surface attributes in this series are defined by color and surface state. The processing procedure of the input parameter determination program can be divided into a “pre-processing” part (left half of FIG. 1) and a “main processing” part (right half of FIG. 1). First, the processing procedure of the “pre-processing” portion will be described.

[Input Data i1] First, a reflection model equation is input as one of the input data. This reflection model formula is used in the illumination simulation program. For example, when a plurality of the models are prepared, one of them is selected. Here, the following reflection model formula is used.

(Equation 1) This reflection model formula is expressed as Diffuse reflectanc
e) and the specular reflectance component. The parameters are (a ₁ , a ₂ , a ₃ , a ₄ ,
a ₅₎ it is five. Diffuse reflection assumes a simple model called Lambert's cosine law. Lambert's cosine law has been reported to deviate from the law for surfaces with severe irregularities, especially at low angles (M
ichael Oren, Shree K. Nayar, Generalization of Lamber
t's Reflectance Model, Computer Graphics Proceeding
s, Anual Conference Series, P239, 1994). However, it can be said that physical phenomena can be sufficiently expressed depending on the level of approximation. The use of this rule means that the dependence of the incident angle is predetermined. Therefore, in the first embodiment, of the measured data in the input data i2 to be described later, the data relating to the incident angle dependency is unnecessary. Here, it is assumed that the value is represented by an incident angle of 45 °. (A ₁ , a ₂ , a ₃ ) represents the average color balance of the surface by RGB components. Also,
The specular reflection component is represented by a Gaussian distribution approximation. a ₅ is its standard deviation. Furthermore, a ₄ represents the ratio of specular reflection to the entire reflection. Therefore, in the above-mentioned reflection model formula, (a ₁ , a ₂ , a ₃ ) is a parameter relating to color, and (a ₄ , a ₅ ) is a parameter relating to a surface state which defines specular reflection.

[Input data i2] Further, the hue, saturation, lightness, surface state,
Angular distribution data ρ _prf (λ, λ) of the spectral reflectance of each sample measured for at least three samples in which only one condition is different for each of the five conditions of the incident angle.
θ) is prepared. That is, three samples differing only in hue,
Prepare data ρ _prf (λ, θ) of (reflectivity ρ _prf ) vs. (wavelength λ) vs. (reflection angle θ) for at least 15 types of samples, such as three samples that differ only in saturation. I do. However, among the above 15 types of data, there may be cases where conditions overlap, so the actual number of data may be smaller than this. Further, in the first embodiment, as described above, since the reflection model formula itself used as the input data i1 has dependency on the incident angle, measured data on samples having different incident angles can be omitted. Incidentally, measuring devices for these data are currently installed in some research facilities, and for example, it is possible to measure using them. In the first embodiment, a sample was selected in which three different values for each of the above conditions were evenly separated. For example, the hue is 120 ° out of 360 ° of the hue circle.
The samples were chosen to be at intervals. Since the saturation and lightness are not circular, the samples were selected so that they were equally spaced in the range of possible values. Regarding the surface condition, the coating industry shows 10 levels (all luster, ..., 5 min luster, 4 min luster,
…, Matte), but these are JIS Z87
It can be replaced by the specular gloss at 41. The incident angle is omitted because the reflection model itself has the dependency on the incident angle as described above. The angular distribution of the spectral reflectance obtained for each sample is from 390 nm to 7
It is measured at every 10 nm step up to 30 nm. FIG. 3 shows an example of actually measured data of the angular distribution of the spectral reflectance of a certain sample. The figure shows the reflection angle θ (−80 to
The relationship between the wavelength λ and the reflectance ρ _prf is shown for each (80 °, 10 ° increments).

A list of actually measured samples is shown in the following table.

[Table 1] In Table 1 above, the first sample (A1B2) for the hue, the second sample (A1B2) for the saturation, the third sample (C5D1) for the lightness, and the first sample (C5D) for the surface state
Since the sample is the same as 1), the actual number of samples is 1
0. It should be noted that the above-mentioned angular distribution data of the spectral reflectance requires a certain amount of time for the measurement, and there is no publicly available database at present, but the hue, saturation, lightness, surface state, incident angle, etc. For each condition, it is sufficient to measure the angular distribution of the spectral reflectance for at least three different samples, so do not make any measurements such as making actual prototypes for the surface colors of ready-made products or products to be made. In this respect, it can be said that it is more realistic than the second conventional technique, and is easily spread in a wider field.

[Steps s1 to s5 (corresponding to a spectral reflectance data conversion step and a parameter dependency information generation step)]
Subsequently, processing using the prepared input data is started. First, the angular distribution data ρ _prf (λ, θ) of the spectral reflectance for each sample prepared as the input data i2 is converted into the XYZ color system using the following equation under the white light (an example of the reference light). (Step s1).

(Equation 2) Here, since white light is used, S (λ _j ) in the above equation is λ
It is 1 (constant) regardless of _j . The using white light in the first embodiment, when the simulation with a color light source, the calculation (step s13 and s15 will be described later) is to become a simpler, any light course D _65, etc. May be used as the reference light.

Next, X, Y, and Z of the XYZ color system are represented by
Linearly converting to an RGB coordinate system (an example of a predetermined coordinate system relating to the coloring of a material, the same applies hereinafter) by the following equation (step s)
2).

(Equation 3) The above matrix H is obtained by setting white light as White Point,
This is calculated using the values of the three primary colors of CIE. For the reference light, other lights may be used as long as they are unified throughout the entire process. Of course, the values of the three primary colors can be used as long as they are unified, for example, the values of the display-specific three primary colors. May be used. Here, the three primary colors of CIE are used because the aim is to perform pure reflectance calculation independent of the output model when converting from XYZ to RGB, and it is not possible to perform conversion outside the area. This is because there is little possibility that a color will appear. In the paper (Hideki Tajima, "Study on Color Reproduction Method by CG under Low-pressure Sodium Lamp Illumination", which was taken up as the third prior art described above, Journal of the Illuminating Engineering Institute of Japan, Vol. 80, No. 8A, 1996). Although the three primary colors of the color television standard (NTSC) are used, since the display range of the display is narrow,
Many colors that cannot be converted in the XYZ display system have appeared. In this case, the value is negative when converted formally, but in this paper the value is approximated as 0. It is considered that one of the causes of the error of the three-band method pointed out in this paper is here. In the first embodiment, the correction of each display device (display) is left to the post-process (post-processing) after the simulation, and the pre-process (input parameter determination process according to the present invention) does not depend on the display device. In order to perform pure reflectance calculation processing, the three primary colors of CIE, which have few errors (colors outside the above-mentioned region) and have no machine dependence, are used as much as possible. Thereby, the error of the luminance calculation result of the three-band method is reduced.

Subsequently, the reflection model formula of the input data i1 is fitted to the data group of the RGB coordinate system for each sample obtained in step s2 by regression analysis, and the parameters (a ₁ , a ₂ , a ₃ , a ₄ , a
The optimum value of ₅ ) is obtained (step s3). The method used for the regression analysis may be any method, such as the least squares method. However, since the reflectivity angle distribution varies by two to four orders of magnitude depending on the angle, the fitting is large. Weighting, or minimize the absolute value of the difference other than the least squares method, so that it does not deviate too much from the measurement point of the specular reflection component, i.e., the value of the diffuse reflection component. It is desirable to use a method of performing such operations. In the first embodiment,
The least-squares method was used as a method of the regression analysis.

An example of the parameter dependency information obtained in step s3 will be described. FIG. 4 is a graph showing the relationship between the surface state of the sample and the optimum (a ₄ , a ₅ ) in terms of the specular glossiness generally used in industrial products. However, some materials cannot be represented by the dependence of the specular glossiness, but in such a case, they may be defined by a probability distribution curve of the angle of the elementary surface of the surface which is directly related to the specular reflection. In addition, as a result of checking samples having different hues, saturations, and lightnesses (step s4), it was found that the difference in the conditions of these colors did not affect (a ₄ , a ₅ ). This is clear in theory. However, even if it seems to be the same kind of material, when actually measuring it, it is conceivable that some difference in the composition of the material may have some effect, so in order to confirm reliability, samples of these different colors It is effective to check for

The relationship between the surface condition of the sample and the optimum (a ₄ , a ₅ ) was obtained as described above. Subsequently, the relationship between the data relating to the color of the sample and the parameters (a ₁ , a ₂ , a ₃ ) relating to the color in the reflection model equation is obtained (step s5; corresponding to a relational expression acquiring step). The relationship between the color parameters (a ₁ , a ₂ , a ₃ ) and the value of the diffuse reflectance at the time of actual color measurement can be obtained by making the reflection model formula take an extreme value. That is, a parameter value in a state where only specular reflection is present but no specular reflection is input to the reflection model formula. For the angle of incidence of light,
Enter a value as defined (eg, 45 °). Specifically, the following is performed. Incident light -45 with respect to the sample surface normal
The condition of receiving light at 0 ° and 0 ° is the condition at the time of most colorimetry.
The diffuse reflectance value at this angle (that is, the reflectance value at the time of color measurement) is defined as a vector of three RGB components, and R (0 °) = (R
₁ , R ₂ , R ₃ ), in the first equation of equation (1), the limit value ρ _s = 0, and from the relationship between the incident angle and the light receiving angle,

(Equation 4) In addition, since P = (1,1,1), the second value of the expression (1)
Substituting the equation into the first equation gives the parameters (a ₁ , a ₂ ,
a ₃ ) = C is expressed as a function of a ₄ as follows.

(Equation 5) The relational expression (4) between the color and the surface state of the sample and the parameters obtained as described above is stored in the storage unit 8 as parameter dependency information. This relation is
In the subsequent processing, R (0 °) of the color to be simulated, that is, the reflectance value at the time of color measurement, is determined, and obtained from the correlation data between the surface state and the optimal (a ₄ , a ₅ ) created in the preprocessing. by substituting a ₄ that is, used to wind that determines the _{(a 1, a 2, a} 3). As will be described later,
The RGB values relating to the apparent color of the material under a certain light source can also be substituted for this R (0 °) and processed in the same manner. However, since the computer is not good at solving the algebraic expression analytically as described above, the limit value and the reflectance value at the time of colorimetry are given in equation (1), and the numerical solution is performed. An existing algorithm to be added may be added.

The processing of steps s1 to s5 using the input data i1 and i2 described above is the "pre-processing" part in the present input parameter determination program, and if executed once, is input as the input parameter i1. There is no need to do this again unless the reflection model equation is changed. Subsequently, a processing procedure of a “main processing” portion (corresponding to a parameter value calculating step) in the present input parameter determination program will be described. In this “main processing”, the conditions regarding the color and surface condition of the target material surface are input, and these are applied to the parameter dependency information obtained in the “preprocessing”, for example, the characteristic curve is interpolated. , Extrapolation, etc., and output a set of parameters that best approximate the target material surface as the final result. Note that this “main processing” portion needs to be performed each time before performing the processing by the illumination simulation program.

[Input Data i11 to i13] First, the material surface and the light source to be simulated by the illumination simulation program are input. In the first embodiment, the following material Sample1 is used (input data i11, i12).

[Table 2] As a light source, a high-pressure sodium lamp of a certain manufacturer is assumed. The spectrum referred to the catalog value of the manufacturer (input data i13).

[Steps s11, s12] Input data i
After the input of 11 to i13, the data regarding the color of the material surface (input data i11) is converted into a spectral reflectance distribution R (λ). This value may be considered as a value (spectrum) of diffuse reflection with respect to the wavelength (λ) of the corresponding color. By converting the data on the color of the material surface into the state of the spectrum in this manner, steps s13 and s1 described later are performed.
At 5, the color under the light source can be freely calculated by multiplying with the spectrum of the light source. The conversion is performed by, for example, (Hiroaki Sidegaki, “Analysis of Spectral Reflectance Distribution of Munsell Color Chart”, Journal of the Japan Society of Color Science, Vol. 7 No. 4 (198
It can be performed using the method announced in 3)) (step s12). In this case, since it is necessary to input data relating to the color of the material surface in the X, Y, and Z systems, it is necessary to convert the data by a predetermined method (step s11).
In the first embodiment, since the data on the color of the material surface is given from the beginning in the XYZ coordinate system (Table 2 above), the step s11 can be omitted. For material Sample1 given in Table 2 above, step s1
FIG. 5 shows the spectral reflectance distribution obtained in Step 2.

The subsequent processing is divided into a case where there are a plurality of light sources of different colors in the simulation object and a case where there is only one light source, and performs different processing. The case where there are a plurality of light sources of different colors may be, for example, a case where a scene in which a high-pressure sodium lamp and a mercury lamp are present is simulated. In addition, a simulation in the daytime assuming direct light from the sun and indirect light from the sky corresponds to this. Normally, when a simulation of a light source colored by CG is performed, it is usual to input a value corresponding to a color spectrum as data of the light source to be input to the simulation and calculate the light source (light source characteristics are set to the light source side). How to have it). This method has advantages such as simplicity, easy-to-understand processing, and ability to cope with various types of light sources existing in the simulation target. However, this method is described in the above-mentioned third prior art (Hideki Tajima, "Study of color reproduction method by CG under low pressure sodium lamp illumination", Journal of the Illuminating Engineering Institute, Vol. 80, No. 8A, 1996) However, as described above, it is a fact that a light source having an extreme spectrum has a large error. On the other hand, when the simulation target is light such as a low-pressure sodium lamp or a neon lamp, which has an extreme characteristic consisting of a line spectrum that is far away from the light having a continuous spectrum such as daylight, it is described in the above paper. As described above, if the spectrum of the light source is multiplied by the spectrum of the reflectance of the material on the side illuminated by the light source and the simulation is performed with white light (method of giving the light source characteristics to the reflectance side), the accuracy is improves. However, this method cannot be used when there are a plurality of light sources of different colors in the simulation target. Therefore, in the following processing, when there is only one type of light source in the simulation target, the above-mentioned “method of giving light source characteristics to the reflectance side” is used. The above-mentioned “method of giving light source characteristics to the light source side” is used.

[Step s13] If there is only one type of light source in the simulation target, the process is performed using the "method of giving light source characteristics to the reflectance side". That is, what value the color seen when the material is illuminated by the light source with the reference light in this program is calculated, and the RGB values at that time are obtained. In the illumination simulation program, calculations are performed based on the RGB data and the reference light. Specifically, first, in the above equation (2), S
(Λ _j ) _shows the spectrum of the high-pressure sodium lamp, ρ _brf
(Λ _j , θ _k ) is the Sam obtained in step s12.
The value in the XYZ coordinate system is obtained by substituting the spectrum of ple1 (FIG. 5). Further, RGB is calculated by the above equation (3).
Convert to coordinate system. The resulting RGB values are shown below.

[Table 3]

[Steps s14, s15] When there are a plurality of light sources of different colors in the simulation object,
The processing is performed using a “method of giving light source characteristics to the light source side”. That is, the color that is visible when the material is illuminated with the reference light in this program is calculated, and the RGB values at that time are obtained (step s14). In the illumination simulation program, calculation is performed based on the RGB data and the color of the light source. Specifically, first, in the above equation (2), S (λ _j ) represents the spectrum of white light, ρ _brf (λ _j ,
θ _k ) to Sample1 obtained in step s12.
To obtain a value in the XYZ coordinate system. Then, the data is further converted into the RGB coordinate system by the above equation (3).
The resulting RGB values are shown below.

[Table 4] Further, in this case, it is necessary to convert the spectrum of the light source to be passed to the illumination simulation program into RGB coordinates (step s15). Specifically, first, the spectrum of the high-pressure sodium lamp is substituted for S (λ) in the following equation (5), and the XYZ coordinate values are calculated.

(Equation 6) Here, the value of k is set so that Y of the chromaticity coordinates becomes 100%. The intensity of the light source is input separately based on the specifications of the lighting equipment. Further, the obtained XYZ coordinate values are converted into RGB coordinates using the above equation (3). The calculation results were obtained as follows. X = 116.94, Y = 100.0, Z = 15.07 R = 179.81, G = 83.74, B = 14.37

[Step s16] Subsequently, the RG obtained in step s13 or step s14 is obtained.
Based on the B value, the state of the material surface (for example, glossiness) input as the input data i12, and the parameter dependency information (Equation (4), FIG. 4, etc.) obtained in the “preprocessing”. Then, the parameters (a ₁ , a ₂ , a ₃ , a ₄ , a ₅ ) of the reflection model formula that are optimal for the material are determined. (A
₁ , a ₂ , a ₃ ) can be obtained by applying the RGB values obtained in the above step s13 or step s14 to the above equation (4). Also, (a
₄ , a ₅ ) is obtained by applying the value of the glossiness input as the input data i12 to the characteristic curve shown in FIG. The parameters (a ₁ , a ₂ ,
The values of a ₃ , a ₄ and a ₅ ) are shown below.

[Table 5]

[Table 6] The parameters (a ₁ , a ₂ ,
The values of a ₃ , a ₄ and a ₅ ) are output data of the input parameter determination program, that is, input data of the illumination simulation program. When the light source characteristics are provided on the light source side, the light source color data obtained in step s15 is also input data of the illumination simulation program. Next, the results obtained by the above processing are discussed.

[Regarding Prediction Result of Reflectance Distribution] FIG. 6
Shows the reflectance distribution when the parameters obtained by giving the light source characteristics to the light source side are applied to the reflection model equation for the sample of Sample 1 described above. In FIG. 6, solid lines (R, B, G from the inside)
Are the results obtained by the above processing (hereinafter referred to as estimated values), and ○, Δ, and + are the actually measured data separately measured. The standard error (se) of the estimated value at the specular reflection portion (30 ° to 60 °) is 288.6, which is the s. e. Is 286.6, and the estimated value is almost as accurate as the measured data. The development of such a highly accurate reflectance prediction method in the three-band method is expected to further promote the effective use of lighting simulations in the fields of civil engineering and architecture.

[Results of Lighting Simulation Using This Input Parameter Determination Program as Preprocess]
FIG. 7 shows the result of performing an illumination simulation calculation using the ray tracing method by the illumination simulation program with the input parameter determination program as a preprocess. The five images shown in the figure are a photograph of an actual site and an image obtained by simulating by changing the parameters relating to the surface state of the railing (railing) in four stages. For the photographs of the above-mentioned sites, those baked so as to be closest to visual observation were used. However, it is difficult to compare these images visually because the attached drawings of the present application cannot display in color and the resolution is low. FIG. 8 shows the profile of the brightness of the image data on the straight line AB in the upper part of the high column in each image. From FIG. 8, it can be seen that the simulation result in the case of all gloss is closest to the photograph of the site in the entire range from point A to point B. Conversely, when the parameters relating to the surface state are variously changed, it can be seen that the image greatly changes as shown in FIG. Conventionally, intuitively inputting parameters relating to the surface state that greatly affects the appearance in this way, but this result also proves that this greatly impairs the reliability of the simulation.

As described above, in the input parameter determination method according to the first embodiment, the color of the material, the surface state, and the like are obtained by fitting them to the reflection model using the minimum required measured data. In order to determine the optimal parameters for the reflection model equation by generating the parameter dependence information of the reflection model equation for Even without a high-performance computer or expensive measuring equipment, or even without a person skilled in the art, it is possible to obtain optimal parameter values that are easily and quickly, and that are physically based, It is possible to perform a highly accurate optical simulation.

(Modification of First Embodiment) Step s
In step 3, if the standard error of the estimated value obtained by the fitting process by the regression analysis (an example of a predetermined value representing the degree of fitting) is output, the reflection model equation input as the input data i1 The degree can be used to determine whether the actual reflectance value can be approximated. Thus, for example, inputting a plurality of available reflection model equations, comparing the standard errors,
It is also possible to select the most appropriate reflection model formula.
When the input parameter determination program is an independent program separate from the illumination simulation program as in the first embodiment, not only the reflection model formula included in the specific illumination simulation program but also an arbitrary reflection model Since it is possible to input an expression, it is possible to compare and examine the reflectance input value between different illumination simulation programs.
Of course, even when the input parameter determination program is incorporated as a pre-processing routine in the illumination simulation program, a reflection model formula other than that assumed by the illumination simulation program may be input. In any case, by using the above-mentioned input parameter determination program that can determine the input value of the reflectance based on a certain standard that does not contain the intention of the manufacturer, it is possible to use different illumination simulation programs. Even so, the level of the reflectance input value, which is a prerequisite for the simulation calculation, can be made uniform, and conditions for cooperative activities and competitions between various organizations to be smoothly performed are established. In the above example, the fitting of the reflection model equation (three-dimensional) in step s3 is performed two-dimensionally by reducing the dimension by one in order to simplify the processing. It goes without saying that it is good.

(Embodiment 2) The problem B described in the section of the problem to be solved can be solved by using the input parameter determination program according to Embodiment 1 described above. That is, when the image data is created using the CG software, the color specified by the user can be reproduced on the computer by using the parameters calculated by the input parameter determination program according to the first embodiment. That's why. Therefore, in the second embodiment, the input parameter determination program according to the first embodiment and the Apple Computer, In
c. ColorSync or its equivalent program is integrated, and the above two problems A and B are solved together, and the image data (image data) containing the color (industry standard, etc.) intended by the sender is received by the receiver. A description will be given of an image data transmission program that enables accurate transmission to the user.

The image data transmission program according to the second embodiment is, as shown in FIG. Here, the process is
The process is performed on the image sender side, and the process is a process performed on the image receiver side. That is, it is necessary to install this image data transmission program on each computer of the sender and the receiver of the image.
It is to be noted that only the processing program of the steps (1) to (4) may be installed on the sender side, and only the step and the processing program may be installed on the receiver side. However, in this case, transmission and reception in the opposite direction cannot be performed. Also, a computer on the sender side (not necessarily a computer on which the image data transmission program is installed) is provided with a CG for generating an image.
Software must be installed, and e-mail client software for transmitting and receiving image data must be installed on each of the computer on the sender side and the computer on the receiver side. Note that, of the above steps 1 to 5, the steps correspond to the input parameter determination program according to the first embodiment. In addition, regarding the above steps,
Although it is possible to use ColorSync of Apple Computer, Inc. mentioned above, at this time, Apple Computer, Inc.
Since ColorSync, which runs on computers other than the above, has not been released, we used a method derived from basic knowledge of color engineering. The image data transmission program is, for example, a WWW browser software (Netscape Communi
cator, Microsoft Internet Explorer, etc.). Hereinafter, the steps shown in FIG.
Each will be described in detail.

Generation of Correction Information Data In this step, the sender generates correction information data to be transmitted to the receiver together with the image data created by the CG software. Below, (a) Indoor environment setting, (b)
The setting of the gamma value of the output device, the setting of (c) the white color of the output device, and the setting of the three primary color values of the output device will be described separately.

(A) Indoor environment setting In this indoor environment setting, when a person sees a color in a state of adaptation under a certain illumination, and when the illumination is different from the standard condition, how the human looks different from the standard condition. Set the correction data for correction. Such a correction method is described in a standard document of the International Commission on Illumination (CIE) ("AMethod of Pr
edicting Corresponding Colorsunder Different Chro
matic and Illumination Adaption ", Ref.:Publ.CIE 10
9-1994). This method is different from the design office, the maker, the office, etc. where the computer will be placed, as will be applied from now on, and it can be implemented precisely under extremely controlled and limited conditions. However, by treating this as an approximation, the indoor environment of each user can be effectively corrected. Input value in the above method,
The relationship between the output values is as follows. Since the details of this calculation are complicated and need not be mentioned here, it is replaced by the function F1. (x2, y2, Y2) = F1 (x02, y02, E02, x01, y01, Y0, E01, x1, y1, Y1) ... (11) The meaning of each symbol in the above formula (11) is as follows: It is. (x1, y1, Y1): Numerical value representing test color E01: Illuminance of test illumination (lx) (x01, y01, Y0): Color of test illumination (x2, y2, Y2): Numerical value representing standard color E02: Standard Illumination of illumination (lx) (x02, y02, Y0): color of reference illumination

Here, in the case of the present invention, the meanings of the above symbols are replaced with the following meanings. (x1, y1, Y1): Numerical value representing the color obtained by the sender E01: Illuminance of the illumination at the place where the equipment on the sender side exists (lx) (x01, y01, Y0): Equipment on the sender side exists The color of the lighting at the location where the receiver is located (x2, y2, Y2): the color value that should be the same color as seen by the sender on the receiver side E02: the illuminance (lx) (x02, y02) of the lighting where the receiver device is located , Y0): Color of lighting at the location where the receiver's device exists However, as a practical matter, the user can only grasp the indoor lighting as follows. -Types of lighting (not accurate such as color, but vague such as fluorescent lamps and incandescent bulbs)-Room brightness (bright, dark, ordinary, etc., but there are standards in company offices) , In general
It is in the range of 300lx to 2000lx. As described above, since what the user can understand about indoor lighting is, after all, summary information, here we will use the International Commission on Illumination rather than using it correctly to make corrections. It should be considered mainly. The user is required to input the following items regarding the indoor environment through a dialog box as shown in FIG. -Lighting type (fluorescent lamp, incandescent bulb, northern window daylight, etc., selected by choice box)-Indoor brightness (dark, normal, bright selected continuously by slider bar) And actually these values When used for calculation, for example, the following is performed. -Lighting type: The color of each representative lighting is stored in a computer and used.・ Indoor brightness: 300lx (dark), 1000lx (normal), 20
00lx (bright), and the intermediate value is replaced linearly. By the above processing, the color value (x0
1, y01, Y0) and the illuminance value E01 of the illumination on the sender side are set.

(B) Setting of gamma correction value of output device Setting of gamma correction value of output device is a well-known fact that is also found in a textbook of image processing engineering. In addition, the number C
G-software (for example, Adobe Photoshop) has such a function. Therefore, although the detailed description of the principle is omitted here, the gamma correction value is for correcting the nonlinearity of the output intensity of the output device, and is represented by one real value (gamma). For the correction formula, R, G, B
For each input intensity int, the correction intensity out is expressed in the form of a power of out = intt (1 / gamma) (12). Where int and out are 0
If it is represented by an 8-bit numerical value from 0 to 255, it is multiplied by 255 and rounded to an integer value. The setting input of the gamma correction value can be performed using, for example, a dialog box as shown in FIG. That is, the position of the slider bar is adjusted so that the vertical stripes in the dialog shown in FIG. 12 disappear, and the OK button is pressed. The value obtained by this is one real number from 1 to 3 (hereinafter referred to as gamma). In the case of a general display, it is often around 2. Through the above processing, the gamma correction value gamma of the output device is set.

(C) Setting of the white point of the output device This is to determine which point on the chromaticity coordinates (x, y) corresponds to an achromatic color (that is, gray without red, yellow, and green). To set. The user adjusts the x and y slider bars in a dialog box such as that shown in FIG. However, this adjustment is difficult if you are not used to it.
In a normal display, a white point is represented by a color temperature. In the case of CIE daylight, this color temperature is calculated from the color temperature to the chromaticity coordinates (x_
D, y_D) is defined (JIS: Z87
20). So, first, move the color temperature slider bar at the top of the dialog box, find the place where the central gray scale is the least colorless, and fine-tune with the x, y slider bar. . Let the value of the white point position obtained here be (Wx, Wy). How to reflect this value in the conversion will be described in the next section (d) Setting of three primary colors of the output device.

(D) Setting of three primary color values of the output device The three primary color values characterize the color characteristics of the output device, and the chromaticity coordinates (x, y) of the three primary colors R, G, and B , Represented by a total of six real values. For inputting this value, for example, a dialog box as shown in FIG. 14 can be used. In this dialog box, real colors close to the primary colors are displayed for the R, G, and B colors. These three colors are colors represented by Munsell symbols. The user holds the equivalent color on the Munsell color sample in his hand, and adjusts the x and y slider bars of each color so that the color on the screen matches the color sample. If this is troublesome, the value at the time of shipment from the manufacturer of the output device may be referred to. In order to cope with such a setting method, in the dialog box shown in FIG. 14, values for each model number of several manufacturers are prepared in a choice box. The three primary color values obtained here are Rx, Ry, Gx, Gy, Bx, and By. These six real values, together with Wx and Wy obtained earlier, are used to convert xyY to RGB values used on a computer. This conversion method is also a general knowledge in color engineering, and is described in, for example, (Noboru Ota, “Color Engineering”, Tokyo Denki University Press, Tokyo, (1993) P100). Since this conversion method cannot be expressed by a simple function,
Here, it is expressed as follows. (X, Y, Z) = F2 (x, y, Y)… (13) (R, G, B) = F3 (Rx, Ry, Gx, Gy, Bx, By, Wx, Wy, X, Y, Z) (14) Since these transforms are reversible, there are also inverse transforms. That is, (X, Y, Z) = F3 ＾ (-1) (Rx, Ry, Gx, Gy, Bx, By, Wx, Wy, R, G, B)… (15) (x, y, Y) = F2 ＾ (-1) (X, Y, Z)… (16)

Thus, the generation of the correction information data for the process is completed. That is, in this process, x01, y01, Y
0, E01, x02, y02, E02, Rx, Ry, Gx, Gy, Bx, By, Wx,
Each value of Wy, gamma (where x02, y02, and E02 are values set on the receiver side and are blank at this time) were set as correction information data.
In the pull-down menu, environment setting / environment setting tour shown in FIG. 10, the four dialog boxes shown in FIGS. 11 to 14 are sequentially displayed while introducing them, and the user is requested to input. As a result, even a novice user who has no knowledge of color engineering and image processing engineering can easily make settings.

A color simulation for colors and light sources is performed, and data for various CG software is output. This step corresponds to the processing by the input parameter determination program according to the first embodiment. However, here
"Pre-processing" in the above input parameter determination program
It is assumed that the part has been executed in advance, and only the “main processing” part will be described. Since the details have already been described in the first embodiment, only the outline will be described here. In addition, there is a part where the processing needs to be partially changed depending on the CG software used in the image generation processing on the downstream side. In this case, the processing is branched depending on the type. Here, (i) a program that performs lighting simulations such as RADIANCE manufactured by the LBL (Lawrence Berkeley Lab. Affiliated Laboratory of the University of California, USA), faithfully calculates the surrounding environment such as the light source, and displays the resulting colors (ii) ) Adobe Photoshop, Autodesk 3D Studio, etc.
Consideration was given to the case of using two types of CG software, a program that directly expresses colors. In the following description, it will be referred to as type (i) CG software and type (ii) CG software.

(E) Input of light source type (corresponding to input data i13 in FIG. 1) First, the type of light source is input using, for example, a dialog box as shown in FIG. The type of light source can be selected from natural daylight and artificial light. Here, the daylight function formula of CIE is used as natural daylight (JIS: Z87
20). Since this is a function using the color temperature as a variable, the color temperature slider bar allows the user to set the color temperature (unit).
K; Kelvin). In addition, general values such as 10000 K in the daytime and 6000 K in the evening are set in the choice box so that users who are not accustomed to color temperature can easily set them. In the program
After entering the color temperature, the light source characteristics are replaced with a spectrum (a graph of the frequency dependence of light intensity) because CIE has a formula for calculating daylight. Also, for artificial light sources, the program has spectral data provided by the lighting manufacturer, and the user can select the lighting equipment name in the choice box to call up the corresponding spectral data. I have. The spectrum of the light source obtained here is represented by ρs.

(F) Surface state input (corresponding to input data i12 in FIG. 1) This surface state input is necessary only for output to type (i) CG software. For the input, for example, see FIG.
A dialog box as shown in FIG. 6 can be used. Here, by inputting the reflection characteristics of solid color paint as gross (JISZ8741) or its equivalent paint finish step standard (full gloss, half gloss, matte, etc.), the solid angle distribution of the reflectance in internal processing Converted to dependency data. Specifically, the gloss is converted into the parameters of the reflection model using the characteristic data as shown in FIG. The reflection model given the parameters exactly represents the solid angle distribution dependence data of the reflectance. The parameter scalar or vector obtained here is represented by gs.

(G) Input using the Munsell symbol of the object color or a color chart symbol of another industrial standard (input data i in FIG. 1)
Here, an industrial standard color chart number of a color to be used for design (a color to be expressed in CG) is input. These standards include the Munsell symbol and the color chart number of the Japan Paint Manufacturers Association, etc. Here, the description will be made using the Munsell symbol, which is widely used worldwide. For inputting this value, for example, a dialog box as shown in FIG. 17 can be used. The Munsell symbol expresses a color by three values of H (hue), V (lightness), and C (saturation). Therefore, a slider bar is provided for each of H, V, and C so that the user can make an input. Inside the program, a process of replacing the input Munsell symbol with the spectrum data is performed (corresponding to S11 and S12 in the first embodiment). The value input here is represented by H, V, C.

(H) Display of color data for each CG software As described above, the input values necessary for the color simulation are completed in (e), (f), and (g). Now we move on to the actual calculations. However, here, type (i) CG software, type (ii)
It is necessary to perform processing for each CG software. Hereafter, the CG
This will be described for each type of software.

Type (i): CG software for performing illumination simulation In illumination simulation, characteristics related to the basic color appearance of a material, called diffuse reflection, and shine, called specular reflection, are used. Consider characteristics. Therefore, when targeting this type of CG software, it is necessary to consider both diffuse reflection and specular reflection. The processing is
This has already been described as “the main processing” in the first embodiment. Although this processing is not represented by one simple function, in the second embodiment, for simplicity of explanation,
I will replace it with a function called F4. The processing is represented by the following equation. (a [1], a [2],…, a [n]) = F4 (Rx ', Ry', Gx ', Gy', Bx ', By', Wx ', Wy', ρs, gs, H , V, C) (17) In the above equation (17), the values entered in parentheses on the right side are the parameters for the reflection model output on the left side. The reflection model used here is of course a type
It must be a model of the CG software of (i). If the model formula is publicly available software (for example, Radiance described above), the process can be performed. With the above, the processing of the step in the case of using the type (i) CG software is completed. After that, the obtained value (a [1], a [2],…, a [n])
Is input to the type (i) CG software by the user, and the target image is obtained by calculation. The above (1)
Rx ', Ry', Gx ', Gy', Bx ', By', Wx ', Wy' in equation (7) are Rx, Ry, Gx, Gy, Bx, B as the characteristics of the output device previously set.
Instead of y, Wx, Wy, it is a constant value for conversion possessed by CG software of type (i) (for example, in the case of Radiance, these are published and can be used for calculation). In the first embodiment, these values are replaced by the matrix H, but they may be considered equivalent. Using these values,
An image is obtained by performing calculations using CG software of type (i).
The obtained image is corrected by the correction function of the type (i) CG software so as to match the output device. Rx, Ry, Gx, Gy, Bx, By, Wx, Wy,
gamma. These values are not constants of the CG software but are characteristics of the output device.

Type (ii): C for expressing color as it is
G software In this case, of the diffuse reflection and the specular reflection, only the diffuse reflection may be considered. In the first embodiment, the parameters
a [4] = 0, a [5] = 1 among a [1], a [2], a [3], a [4], a [5]
It is equivalent to fixing. In this case, the remaining parameters a [1], a [2], a [3] correspond to R, G, B, respectively. Under these conditions, (1)
Equation 7) is also expressed as follows. (x, y, Y) = F5 (ρs, H, V, C) (18) Here, note that the parameter gs representing the surface state has disappeared. The need for specular reflection is no longer required. Next, using the various parameters set in the environment settings, (x, y, Y)
Convert to (R, G, B). The processing is as follows. Coordinate system conversion by equation (13) ... (X, Y, Z) = F2 (x, y, Y) ... (19) Conversion to RGB by equation (14) ... (R, G, B) = F3 (Rx , Ry, Gx, Gy, Bx, By, Wx, Wy, X, Y, Z) ... (20) Gamma correction by equation (12) ... out = int ＾ (1 / gamma) ... (21) where int , out correspond to the values of R, G, B, respectively. Thus, the processing of the step in the case of using the type (ii) CG software is completed. After that, the user simply inputs the obtained value RGB into the type (ii) CG software and obtains the result. In general, when a design is expressed by CG, a plurality of types of colors are used, so the above-described processing is repeatedly performed for each color.

(I) Display of colors and explanation of colors by diagrams The processing of (I) is for displaying the colors to deepen the user's understanding of the colors. In this dialog box,
As shown in FIG.

Now, the obtained integer values of R, G, and B should fall within a range of 0 to 255 in a 24-bit full color display. However, the range of colors displayed on the output device is narrower than that of colors in the real world. Specifically, for example, when the saturation becomes high, the output device is over-ranged and cannot be expressed. Among the standard colors of the Japan Paint Manufacturers Association, there are many colors that cannot be represented by output devices. As described above, according to the second embodiment, it is desirable to provide a function of outputting a warning when a calculation result that cannot be displayed by the output device is obtained. As a specific example of the method, it is conceivable to issue a warning when the range is over, that is, when any or all of R, G, and B become 0 or less or 255 or more. However, even if a warning is given, it does not mean that this color is not displayed. If it is less than 0, it is approximated with 0, and if it is more than 255, it is approximated with 255. Otherwise, weird images with holes will be output.
In this case, for example, when the user moves the mouse to a point on the image and clicks the mouse, it is desirable that the user can distinguish whether the color is an approximated color. The user
If the point you clicked is displayed as an approximate color, you can know that it was saturated at the time of output. Alternatively, a saturated area and a non-saturated area may be recorded as fourth image information following R, G, B in another image or an image format called an α channel. Such display has not been performed consciously of the output limit of output devices, but when designs are used as criteria for decision making in electronic commerce, this accurate handling is extremely effective. .

As described above, in this section, type (i) CG software,
Type (ii) has been described separately for the CG software, but it should be noted that the correction information data (environment setting data) set in the process is effectively used for the simulation calculation in the process. . As will be described later, the simulation result of the process is processed again using the correction information data. That is, by combining the techniques used in the process with the method as in the second embodiment, the color of the sender (at the industrial standard level) can be accurately transmitted to the receiver. . Appl
In the conventional technologies such as ColorSync of e Computer, Inc., the technology corresponding to the process is used only for color matching on the net. However, it is apparent from the above processing that the present invention is not limited to this. It is clear.

Image Display and Attachment (Embedding) of Correction Information Data After the parameters obtained in the above process are input to the type (i) or type (ii) CG software by the user to generate an image, This step is performed after the image is transferred to the main image data transmission program again. Here, an image generated by the CG software of the type (i) or (ii) is displayed, and further, correction information data is attached to the image data. By the way, the following two cases can be considered when displaying an image.・ If the image is generated by the CG software on the computer using the values obtained in the above process:-> In this case, the displayed image is left as it is without any image correction. With this image, an image of the correct color intended by the user can be obtained. -If the image is not CG software on the computer but is generated on another computer using the values obtained in the above process:-> Correct image is obtained only after image correction Can be Here, this step is a step for the former case. In the latter case, only the steps described below need be performed.
However, the embedding of correction information performed in this step is performed for image correction in the step. It should be noted that the image data transmission program according to the second embodiment is used on both the sender side and the receiver side of the image. By asking the user whether the image correction is made by the computer or is it sent from another computer, it can be determined whether the image correction is “absent” or “present”.

Next, attachment or embedding of correction information will be described. The correction information data to be embedded is, for example, the following 17 real numbers.・ X01, y01, Y0, E01, x02, y02, E02, ・ Rx, Ry, Gx, Gy, Bx, By, Wx, Wy, ・ gamma, ・ ρs The disadvantage is that the number increases by one in addition to the image, but there is the merit that it can be simplified. Embedding requires programming, but has the advantage of requiring only one image file. In the second embodiment, either one is not specified, but here, it is assumed that embedding is performed. Many image formats have an area that can be arbitrarily defined by the user. JPEG, the most popular image format on the Internet, also has an area that can be arbitrarily defined by the user. Literature: Eric Hamilton, JPEG File Interchange For
mat Version1.02, C-Cube Microsystems, September 1,
According to 1992, APP0 in the format identifier
(Application-specific information). In many other image formats, a comment area is secured in many cases, and the correction information data can be embedded in the area. The format for embedding may be a bytecode representing a real value, or a bytecode of a text string representing a real value. Thus, the process is completed. Later, the sender uses Netscape Communicator, Microso
ft E-mail may be sent to the recipient using an Internet mail client such as Internet Explorer or Outlook, may be copied to media such as a floppy (registered trademark) disk, mailed, or published on the Web. ,
The recipient may download it from here. Upon receiving image data (including correction information data) sent from the sender by e-mail, for example, the receiver performs the following process.

Generation of Corrected Image Information on the Recipient Side The operations performed here are almost the same as those in the above steps, and differ only in the following two points. -Whether the sender or the receiver performs-The variable set that contains the indoor environment data is x01, y01, E01
It is simply x02, y02, E02. Therefore, detailed description is omitted here.

Image correction and display on the receiver side The fact that (x, y, Y)-> (R, G, B) conversion can be performed from the correction information has already been described in the above equations (18) to (21). . (x,
(y, Y) can be called real world color data, and (R, G, B) can be called virtual world color data on a computer or a network. The method of image correction will be described with reference to FIG. Now, the conversion from real to virtual color data generated from the correction information attached to the image file created on the sender side is represented by an operator A. The conversion from the real to the virtual color data created on the receiver side is represented by an operator B. This real world color data
(x, y, Y) <-> The conversion of virtual color data (R, G, B) is reversible. Therefore, the operators A and B have an inverse (inverse transformation). Now, let the inverse transform of A be called A ＾ (-1). When the image data is transferred from the sender to the receiver, as described above, the image data is transmitted in an existing image format such as JPEG, that is, virtual color data (R, G, B). What the image data recipient does is: -The virtual color data (R, G, B) sent to A ＾
The color data (x, y, Y) in the real world is temporarily restored using (-1). (R1, G1, B1)-> (x1, y1, Y1)-This is adjusted to the receiver's indoor environment by the chromatic adaptation conversion (let it be an operator F1) of the above equation (11). (x1, y1, Y1)-> (x2, y2, Y2) ・ Return to the appropriate image on the output device on the receiver side with operator B (x2, y2, Y2)-> (R2, G2, B2) By filtering the image using the B ・ F1 ＾ A ＾ (-1) conversion, the receiver can see an image having the same color as the image seen by the sender.

When an arbitrary point on the displayed image is clicked with the mouse, a value (xyY or Munsell symbol) corresponding to the color data of the color in the real world can be displayed. It is. This is to read the RGB at the clicked position and perform the inverse transformation of B F1F (-1) · B ＾ (-
It can be easily realized by multiplying by 1). This gives
It can output the value of xyY. Further, the above (18)
By performing the inverse transformation of the equation, it is possible to output an approximate Munsell color chart number. Of course, if the color of the point is a saturated color that was warned in the above process, instead of returning the calculation result, a display indicating that it is a saturated color and cannot return an accurate value will be displayed. What should I do? As a result, the recipient is not just an image,
Get very specific information. Displaying such specific image information with consideration has not been performed so far. When a design is used as a criterion for decision making in e-commerce and the like, accurate handling of such image information is extremely effective.

(Specific Example of Embodiment 2) As a specific example,
An example in which the program described in the second embodiment is installed on two different computers and used by a user will be introduced. ≪1. Equipment and Environment Conditions The conditions of the display devices P and Q of the two computers used in this example are as follows.

[Table 7] Further, CG software shown in the following Table 8 was installed in the computer P. Therefore, the device P is on the sender side (CG data producing side) and the device Q is on the receiver side.

[Table 8] The device P and the device Q are connected by an in-house LAN, and the communication software (e-mail client)
We used Netscape Communicator. Table 9 below shows the environment in which the devices are placed. The devices P and Q were both placed in the indoor condition 1.

[Table 9]

{2. Measurement Sample >> The chromatic Munsell colors used as samples are shown in Table 10 below.

[Table 10] FIG. 20 shows the position of the Munsell color in the xy chromaticity coordinate system.

{3. Implementation Procedure >> First, the program of the second embodiment was installed in the computers of the devices P and Q, so that the user could operate it from the GUI on the window system of the operating system. Hereinafter, the work on the device P on the sender side will be described in section 3.1, and the work on the device Q on the receiver side will be described in section 3.2.

(3.1 Work on the Device P on the Sender Side) The device P on the sender side was placed in a room under indoor condition 1 (fluorescent light, normal brightness). As can be seen in FIG.
Operations performed by the sender are divided into operations performed by the program according to the second embodiment and operations performed by CG software. First, the user on the sender side is caused to perform the steps in accordance with the instructions of this program according to the procedure described in the second embodiment, and to input the steps for each sample color in Table 10, and to input data relating to the colors. I got it. Next, using the color data, the type (i), type (ii) -1,
(ii) A CG was created using the CG software of -2. C created
The shape of G is the type (ii) -1 two-dimensional CG software,
As shown in FIG. 21, the flat plates were arranged. The colors of the samples in Table 10 were sequentially colored on the flat plate. type
In case of 3D CG software of (i) and type (ii) -2, Fig. 2
As in Fig. 2, spheres were created together with flat plates, and each was colored. The order of coloring is the same as that of FIG.

Since the image processing method of each CG software is different from the principle thereof, the procedure will be described only for the portions necessary for explaining the present invention separately for each software.・ Type (i) (RADIANCE): Lighting data is 45 for white light.
° The working plane was set to be 1000 lx upon incidence. The viewing direction was the front (0 ° light reception). Under these light source conditions, an optical simulation was performed to obtain an image. In addition, RADIAN
The three primary colors, white point, and gamma of the device P were input to image correction software attached to CE, and a corrected image was obtained. -Type (ii) -1 (Photoshop): The value obtained by the program of the second embodiment was directly input. -Type (ii) -2 (3D Studio): The same color values used in Photoshop were directly substituted for the attribute values of the objects in the CG. The light source used white parallel light, the incident angle was 45 °, and the viewing direction was front (0 ° light reception). Regarding the intensity of the light source, N-10, that is, the material of R = G = B = 100% (in this case, the surface on which the sample is placed) is rendered just white (R = G = B = 255) after rendering. The light intensity was adjusted to be displayed. The adjustment of the intensity of the light is a necessary operation when the color is accurately represented by three-dimensional CG software which does not simulate the light accurately as in the type (i).
The user on the sender side reads the three pieces of image data obtained above again into the program according to the second embodiment, and the user selects “File / Save” from the pull-down menu to execute the process, That is, the correction information is automatically embedded. The sender user then attached the three image data to the mail using Netscape Communicator and sent it to the recipient user. (3.2 Work on Receiver Q) The receiver user received the three images on the receiver Q. Thus, it is assumed that the receiver user operates the program of the second embodiment on the device Q to observe the image. The process on the receiver side is performed by the guide of the program similarly to the previous sender side, and the process is automatically performed inside the program.

{4. Measurement result >> If the indoor environment setting of the device Q is different from that of the device P, when the colors on the displays of the two devices are measured by the measuring device, the measurement results are different in principle. However, when humans compare them, they are expected to look the same. This is because the chromatic adaptation characteristics of a human are included in the calculation due to the indoor environment setting. Therefore, in order to enable evaluation by a measuring device, the device P on the sender side and the device Q on the receiver side are placed in the same indoor environment 1 so that comparisons as equivalent physical quantities can be made. FIG. 23 shows an area in which the recipient who has received the image receives the warning display indicating "saturated". this is,
Indicates the color area when some of R, G, B are less than 0 or more than 255. At the business level, since it is not sent to the recipient without being hollowed out just because it is saturated, as described in the second embodiment above, it becomes 0 when it becomes 0 or less, and it becomes 255 when it becomes 255 or more. Transferred close to 255. The measurement of each display P and Q was performed using the color difference meter. FIG. 24 shows the chromaticity of each sample in terms of hue (H), lightness (V), and chroma (C). The figure shows the values of the sample, the value of the device P, and the value of the device Q. Also, for each of P and Q,
The results for type (i) and type (ii) are shown (type (i
i) has two softwares, but the results were almost the same, so they were represented by the value of type (ii) -2). Looking at the measurement results, the actual color, the device display color on the sender side, and the device display color on the receiver side match very well for both type (i) and type (ii) software. However, saturated 5B4-8,5G
For 4-8 and 5R4-14, the deviation from the actual value is slightly large.
This is because the colors are approximate.

{5. Comparison with conventional technology >> Processing equivalent to the above specific example was performed using only color matching on the net without using the present invention. Here, color matching on the Internet refers to, for example, Apple Computer, Inc.
Similar to ColorSync. Since the program according to the second embodiment cannot be used, CG creation on the sender side was performed by trial and error while comparing with a color sample. FIG. 25 shows a measurement result corresponding to FIG. 24 when the present invention is not used. From the measurement results, it can be seen that the following features are provided.・ Device P
And the value of the device Q tend to match.・ However, the actual colors and the colors of the equipment are different. This seems to be an error caused by human visual adjustment.・ There is also a difference between type (i) and type (ii).
This is due to the fact that it is not based on a human-visual adjustment and a physically-based method. As can be seen from the second and third points of this feature, the program according to the second embodiment is described as follows: "The image expressing the design is transmitted accurately on a net or the like, as compared with the related art. Can be said to have been solved successfully. FIG. 26 shows the time required for the CG creation time. The left is the case where the present invention is not used, and the right is the case where the present invention is not used. In particular, the case of the type (i) CG software is prominent. This is type (i)
This is because, for performing an accurate optical simulation, the image calculation time for one trial and error is long. From this graph, it can be seen that the working time is reduced in the present invention. Further, the cause of the time reduction is that the number of trial and error has disappeared. This eliminates the need for skill in trial and error. Furthermore, the task can be easily performed even by a beginner by sequentially teaching the user how to operate the program on the program side. Therefore, it can be said that anyone can easily perform such a work in various places. Further, the function of warning when a calculation result that cannot be displayed in FIG. 23 is output, and the function of returning to the symbol such as Munsell on the receiving side also contribute to accurately transmitting the color to the other party. Further, as described above, there is also an effect of eliminating a color difference between various software. From the above, the present invention provides:
Compared with the conventional technology, “Everyone can easily and quickly convey an image expressing a design on various places, such as on the Internet. 』
It can be said that this problem has been solved.

[0069]

As described above, the first aspect of the present invention simulates the coloring state of an object under a predetermined light source using a reflection model equation having a predetermined parameter. In an input parameter determination method of an optical simulation for determining a parameter value, a spectral reflection is measured for at least three samples, each of which is different from a plurality of conditions including hue, saturation, lightness, and surface state, in at least three samples. A spectral reflectance data conversion step of converting the angular distribution data of the reflectance into a predetermined coordinate system relating to the coloration of the material based on the reference light; and a predetermined process relating to the coloration of the material for each sample obtained in the spectral reflectance data conversion step. The above reflection model equation is fitted to each coordinate system data by regression analysis, A parameter dependency information generating step of obtaining an optimum value of the parameter and generating parameter dependency information indicating a correspondence relationship between the sample and the parameter value; and inputting data on a surface color and a surface state of the object. A parameter value calculating step of calculating a value of the parameter relating to the object based on the parameter dependency information obtained in the parameter dependency information generating step. Because it is configured as an input parameter determination method,
Even without a high-performance computer or expensive measuring equipment,
In addition, even those who do not have skilled craftsmanship on the road can obtain optimal parameter values easily and in a short time and with physical basis, and use them to perform high-precision optical simulation. . In addition, the ability to determine the input value of the physically-based reflectance with a certain standard that does not involve the intention of the manufacturer in this way allows the simulation calculation to be performed even when a different lighting simulation program is used. The level of the reflectance input value that is the condition can be made uniform, and cooperative activities among various organizations,
The conditions to make the competition run smoothly will be set.

The second invention is an image data transmitting method for accurately displaying image data of an arbitrary object created on a computer on the sender side on an output device on the receiver side. Prior to a series of steps relating to the input parameter determination method described in any one of 1 to 5, sender-side correction information for creating sender-side correction information data including environmental information on the indoor and output devices on the sender side An arbitrary image creating means is created based on the data creation step, the sender-side correction information data obtained in the sender-side correction information data creation step, and the parameter values obtained in a series of steps related to the input parameter determination method. After the image data is created by using the above, the sender-side correction information data obtained in the sender-side correction information data creating step is attached to the image data. Is a sender-side correction information data integration step for embedding, a receiver-side correction information data creation step for creating receiver-side correction information data including environmental information on the indoor and output devices on the receiver side, and the sender-side correction information data After the image data obtained in the integration step is transferred from the sender to the receiver by an arbitrary method, the sender-side correction information data attached or embedded in the image data and the receiver And an image data correcting step of correcting the image data based on the receiver-side correction information data obtained in the side correction information data creating step. Therefore, in the transmission of image information, "A: the same image data does not look the same on different computers", "B It is difficult to transfer the color specified by the designer to the computer in a correct way and reproduce it on the computer. " It can be communicated accurately. Further, if a color value obtained by a series of steps related to the above input parameter determination method is out of a range that can be expressed by an output device on a sender side or a receiver side, a warning output is performed, so that a user can perform the warning output. It is possible to always be aware of the output limit of the output device and to handle extremely accurate image data.

If the color value obtained by the series of steps related to the above input parameter determination method is out of the range that can be expressed by the output device on the sender side, the color value is expressed by the output device. Approximate with the possible range of values,
The information of the approximated color value is transmitted from the sender side to the receiver side, or the image data corrected in the image data correction step is displayed on an output device of the receiver side, and optionally. By outputting the actual color information on the color at the designated position, the receiver can obtain not only an image but also extremely specific image information. When the design is used as a criterion for decision making in electronic commerce or the like, it is extremely effective to be able to transmit such specific image information. Furthermore, in each of the above steps, if a setting / input request screen prompting the user for various settings or input is sequentially output, even a novice user who has no knowledge of color engineering or image processing engineering can easily operate. Is possible.

[Brief description of the drawings]

FIG. 1 is a flowchart showing a processing procedure of an input parameter determination program according to Embodiment 1 of the present invention.

FIG. 2 is a block diagram showing a schematic configuration of an input parameter determination device Z1 equipped with the input parameter determination program.

FIG. 3 is an example of measured data of an angular distribution of spectral reflectance.

FIG. 4 shows an example of the relationship between the specular glossiness of a sample and optimal (a ₄ , a ₅ ).

FIG. 5 is a view showing the wavelength dependence of a calculated spectral reflectance of a material Sample1.

FIG. 6 is a reflectance distribution diagram comparing a reflection model equation (solid line) predicted according to the first embodiment of the present invention with measured data (points).

FIG. 7 shows a result image obtained by performing an illumination simulation calculation using a ray tracing method by a certain illumination simulation program using the input parameter determination program according to the first embodiment as a preprocess (the parameter relating to the surface state in the column is changed in four steps). And a picture of the actual site.

8 is a diagram showing a straight line A on a cell in each image shown in FIG. 7;
The figure which shows the profile of the brightness of the image data in -B.

FIG. 9 is a flow block diagram showing a processing flow in an image data transmission program according to Embodiment 2 of the present invention.

FIG. 10 shows an example of a GUI of the image data transmission program.

FIG. 11 is an example of an input dialog box related to indoor environment settings.

FIG. 12 is an example of an input dialog box for setting a gamma correction value.

FIG. 13 is an example of an input dialog box for setting a white point.

FIG. 14 is an example of an input dialog box for setting three primary color values.

FIG. 15 is an example of a light source type input dialog box.

FIG. 16 is an example of a surface state input dialog box.

FIG. 17 shows an example of an object color input dialog box.

FIG. 18 is an example of a dialog box for performing various outputs related to color.

FIG. 19 is an explanatory diagram of image conversion in the image data transmission program.

FIG. 20 shows chromaticity coordinates of the Munsell color used in the specific example of the second embodiment.

FIG. 21 shows a two-dimensional CG in a specific example of the second embodiment.
CG shape created with software.

FIG. 22 shows a three-dimensional CG in a specific example of the second embodiment.
CG shape created with software.

FIG. 23 is a diagram showing a saturated region in a specific example of the second embodiment.

FIG. 24 shows measurement results in a specific example of the second embodiment.

FIG. 25 shows the present invention (the above-described image data transmission program).
Measurement results when only color matching on the net was used without using.

FIG. 26 shows the time required to create a CG according to the specific example of the second embodiment.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 ... Input means 2 ... CPU 3 ... RAM 4 ... Display device 5, 6, 7, 8 ... Storage means 9 ... Bus line

Claims (22)

[Claims] 1. A method for determining an input parameter of an optical simulation for determining a parameter value of an object when simulating a color development state of the object under a predetermined light source using a reflection model formula having a predetermined parameter. , The angular distribution data of the spectral reflectance of each sample measured for at least three samples, each of which is different from the plurality of conditions including hue, saturation, brightness, and surface state, based on the reference light. The spectral reflectance data conversion step of converting into a predetermined coordinate system relating to the coloration of the material, and the data of the predetermined coordinate system relating to the coloration of the material for each sample obtained in the above-described spectral reflectance data conversion step, the reflection model formula is used. The optimal values of the above parameters are obtained by fitting each by regression analysis, and the above sample and the above parameters are obtained. A parameter dependency information generating step of generating parameter dependency information representing a correspondence relationship with the parameter value; input data on the surface color and surface state of the object; and the parameter dependency information generating step. A parameter value calculating step of calculating a value of the parameter with respect to the object based on the parameter dependency information. 2. A method according to claim 1, further comprising the step of obtaining a relational expression for obtaining a relationship between data relating to a color under a certain light source and parameters relating to a color constituting said parameter. 2. The input parameter determination for an optical simulation according to claim 1, wherein the data relating to the color of the surface is converted into data relating to the color under a certain light source, and further converted into the parameters relating to the color based on the relational expression obtained in the step of obtaining the relational expression. Method. 3. A characteristic of a predetermined light source used in the optical simulation when converting the input color data on the surface of the object into data on a color under a certain light source in the parameter value calculating step. When the data is provided on the reflectance side of the object, a calculation is performed based on the characteristic data of the predetermined light source and the reflectance data of the surface of the object, and the predetermined light source used in the optical simulation is calculated. 3. The method according to claim 2, wherein when the characteristic data is provided on the light source side, the calculation is performed based on the characteristic data of the reference light and the reflectance data of the surface of the object. 4. When one kind of light source is targeted in the optical simulation, a process of giving the characteristic data of the light source to the reflectance side of the object is performed, and a plurality of types of light having different colors in the optical simulation are processed. 4. The method according to claim 3, wherein, when the target light source is a target, a process of giving the characteristic data of the light source to the light source side is performed. 5. The optical simulation according to claim 1, wherein in the parameter-dependent information generating step, a predetermined value representing a degree of fitting obtained by fitting the reflection model formula is output. Input parameter determination method. 6. An image data transmission method for accurately displaying image data of an arbitrary object created on a computer on a sender side on an output device on a sender side, the method comprising: Prior to a series of steps related to the input parameter determination method described in the above, a sender-side correction information data creating step of creating sender-side correction information data including environmental information on the indoor and output devices on the sender side;
Image data can be obtained by using any image creating means based on the sender-side correction information data obtained in the sender-side correction information data creation step and the parameter values obtained by a series of steps related to the input parameter determination method. After the creation, the sender-side correction information data integration step of attaching or embedding the sender-side correction information data obtained in the sender-side correction information data creation step to the image data; A receiver-side correction information data creating step for creating receiver-side correction information data consisting of environmental information relating to the output device; and the image data obtained in the sender-side correction information data integration step, wherein the image data obtained in the sender-side correction information data integration step is obtained by an arbitrary method. After being handed over to the recipient
Based on the sender-side correction information data attached or embedded in the image data and the receiver-side correction information data obtained in the receiver-side correction information data creation step,
An image data correcting step of correcting the image data. 7. A warning output is performed when a color value obtained by a series of steps according to the input parameter determination method is out of a range that can be expressed by a sender or a receiver output device. Image data transmission method. 8. When a color value obtained by a series of steps according to the input parameter determination method is out of a range that can be expressed by an output device on the sender side, the color value is expressed by the output device. 8. The image data transmitting method according to claim 6, wherein information of the approximated color value is transmitted from the sender side to the receiver side while being approximated by a value within a possible range. 9. Real color information that can be concretely expressed in an industrial standard or the like regarding a color at an arbitrarily designated position in a state where the image data corrected in the image data correcting step is displayed on a receiving-side output device. The image data transmission method according to claim 6, wherein the image data is transmitted. 10. A three-dimensional computer capable of optical simulation for accurately simulating the reflection of a light source and an object and faithfully reproducing the color of the object under the light source and the environment as the arbitrary image creating means. Without the graphics software and the above simulation,
The image data transmission method according to any one of claims 6 to 9, which is compatible with two-dimensional or three-dimensional computer graphics software for displaying a target color specified by a user as it is. 11. The image data transmission method according to claim 6, wherein in each of the steps, a setting / input request screen prompting the user to perform various settings or inputs is sequentially output. 12. An input parameter determination program for an optical simulation for determining the parameter value of the object when simulating a color development state of the object under a predetermined light source using a reflection model formula having a predetermined parameter. Wherein the input parameter determination program measures at least three samples, each of which has only one condition different from each other for a plurality of conditions including hue, saturation, lightness, and surface state. A spectral reflectance data conversion step of converting the angular distribution data of the spectral reflectance of each sample into a predetermined coordinate system relating to coloration of the material based on the reference light; Each of the above reflection model equations is applied to the data of the predetermined coordinate system for the color development of the material. A parameter dependency information generating step of obtaining optimum values of the parameters by fitting by a regression analysis and generating parameter dependency information indicating a correspondence relationship between the sample and the parameter values; A computer for executing a parameter value calculating step of calculating the value of the parameter relating to the object based on the data regarding the color and the surface state of the object and the parameter dependency information obtained in the parameter dependency information generating step. A computer-readable recording medium characterized by being a medium. 13. The input parameter determination program further comprises: data relating to color under a certain light source;
And causing the computer to execute a relational expression obtaining step for obtaining a relation with a parameter relating to a color constituting the parameter. In the parameter value calculating step, the input data relating to the color of the surface of the object is converted to a color under a certain light source. 13. The computer-readable recording medium according to claim 12, wherein the recording medium is converted into data and further executed by a computer so as to convert the data into parameters relating to the color based on the relational expression obtained in the relational expression obtaining step. 14. The input parameter determination program according to claim 1, wherein, in the parameter value calculating step, the input data relating to the color of the surface of the object is converted into data relating to the color under a certain light source. When the characteristic data of the predetermined light source to be used is provided on the reflectance side of the object, a calculation is performed based on the characteristic data of the predetermined light source and the reflectance data of the surface of the object, and the optical simulation is performed. In the case where the characteristic data of the predetermined light source used in the step (c) is provided on the light source side, the computer is made to execute a calculation based on the characteristic data of the reference light and the reflectance data of the object surface. Item 14. A computer-readable recording medium according to Item 13. 15. When the input parameter determination program targets one type of light source in the optical simulation, the input parameter determination program performs a process of giving characteristic data of the light source to a reflectance side of the target object. If the simulation targets multiple types of light sources with different colors,
15. The computer-readable recording medium according to claim 14, wherein the recording medium is executed by a computer so as to perform a process of giving the characteristic data of the light source to the light source. 16. The input parameter determination program causes a computer to output a predetermined value representing a degree of fitting obtained by fitting the reflection model equation in the parameter dependency information generating step. The computer-readable recording medium according to any one of claims 12 to 15, wherein 17. A computer-readable recording medium storing an image data transmission program for accurately displaying image data of an arbitrary object created on a computer on a sender side on an output device on a sender side, 17. A sender-side correction comprising environmental information on a room and an output device on the sender side prior to a series of steps according to the input parameter determination program according to any one of claims 12 to 16, wherein the image data transmission program comprises: A sender-side correction information data creating step for creating information data, a sender-side correction information data obtained in the sender-side correction information data creation step, and a parameter obtained by a series of steps relating to the input parameter determination method. After the image data is created using an arbitrary image creating means based on the value, the sender A sender-side correction information data integration step for attaching or embedding the sender-side correction information data obtained in the side-correction information data creation step; and a receiver-side correction information data comprising environmental information on the indoor and output devices on the receiver side. After the image data obtained in the receiver-side correction information data creating step of creating the image data obtained in the sender-side correction information data integration step is transferred from the sender side to the receiver side by an arbitrary method, An image data correcting step of correcting the image data based on the sender-side correction information data attached or embedded in the image data and the receiver-side correction information data obtained in the receiver-side correction information data creating step; A computer-readable recording medium for causing a computer to execute the program. 18. The image data transmission program issues a warning when a color value obtained by a series of steps related to the input parameter determination program is out of a range that can be expressed by a sender or a receiver output device. 18. The computer-readable recording medium according to claim 17, wherein the recording medium is executed by a computer to output. 19. The image data transmission program according to claim 1, wherein a color value obtained by a series of steps related to the input parameter determination method is out of a range that can be expressed by an output device on a sender side. 18. The computer according to claim 17, wherein the computer approximates a value within a range that can be expressed by the output device and transmits information of the approximated color value from the sender side to the receiver side. 19. The computer-readable recording medium according to 18. 20. The image data transmission program according to an industrial standard or the like regarding colors at arbitrarily designated positions in a state where the image data corrected in the image data correction step is displayed on an output device on the receiving side. The computer-readable recording medium according to any one of claims 17 to 19, which causes a computer to output real color information that can be expressed. 21. The image data transmission program, as the arbitrary image creating means, accurately simulates reflection of a light source and an object, and faithfully reproduces the color of the object under the light source and environment. 21. A three-dimensional computer graphics software capable of optical simulation and two-dimensional or three-dimensional computer graphics software for displaying a target color specified by a user without performing the simulation. A computer-readable recording medium according to claim 1. 22. The computer-readable storage medium according to claim 17, wherein the image data transmission program causes the computer to execute a setting / input request screen prompting the user to perform various settings or inputs in each of the steps. 22. The computer-readable recording medium according to any one of 21.