JP2002354266A - Image processor, image processing system, image processing method, recording medium, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reduce the deterioration of image quality due to image compression processing by selecting a quantization coefficient matched with the color components of an input image. SOLUTION: A color-space conversion part 201 converts target image data (RGB image signal) into a luminance color difference signal, a color component ratio calculation part 202 calculates the ratio of respective color components of the target image data by using the obtained luminance color difference signal, a quantization coefficient selection part 203 selects a quantization coefficient matched with the target image data on the basis of the calculated ratio of respective color component, and a quantization part 205 quantizes the DCT coefficient of the target image data by using the selected quantization coefficient.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus, an image processing system, an image processing method, a recording medium, and a program. This is suitable for use in an image processing apparatus that compresses

[0002]

2. Description of the Related Art Conventionally, as a compression method for compressing a color still image, JP using discrete cosine transform has been used.
An EG method and a method using Wavelet transform have been frequently used. In these compression methods, the image quality deterioration due to the image compression processing and the compression ratio of the image data are determined by the quantization step of the quantization coefficient for performing the quantization in the image compression processing.

For this reason, for example, in an image composed of a character area and a photographic area other than text, the quantization step of a photographic area where image quality deterioration is not conspicuous is coarsened, and the quantization step of a character area where image quality deterioration is conspicuous is fine. Thus, the image data of the image is compressed. Further, for example, in an image composed of a natural image area and a computer graphics area, the natural image area and the computer graphics area are identified, and the quantization step of the natural image area where the image quality deterioration is not conspicuous is coarsened, so that the image quality deterioration The quantization step of the computer graphics area which is conspicuous is made fine, and the image data of the image is compressed.

[0004]

However, as described above, in the conventional image compression processing, a quantization coefficient which can be applied to various color still images is used as the quantization coefficient. The quantization step of the quantization coefficient is made coarser or finer in accordance with the degree of conspicuousness of image quality deterioration, thereby controlling image quality deterioration by image compression processing and image data compression ratio.

[0005] Therefore, the properties of the input image, especially information on the color components of the input image obtained by color space conversion of the input image, have not been reflected in the quantization coefficients at all. Therefore, in the conventional image compression processing, the quality of the input image, in particular, quantization is performed with a quantization coefficient that is not suitable for the color component of the input image, and there is a problem that image quality deterioration due to the image compression processing may increase. there were.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-described problem, and it is an object of the present invention to select a quantization coefficient suitable for a color component of an input image and reduce image quality deterioration due to image compression processing. The purpose is to be able to.

[0007]

According to the present invention, there is provided an image processing apparatus comprising: image input means for inputting target image data; color space conversion means for converting the target image data input by the image input means into a color space; Based on the target image data subjected to color space conversion by the color space conversion means, a quantization coefficient selection means for selecting a quantization coefficient, and using the quantization coefficient selected by the quantization coefficient selection means, Encoding means for encoding the target image data input by the input means.

Another feature of the image processing apparatus of the present invention is that the color space conversion means converts the target image data input by the image input means into luminance data and color difference data. I do.

Another feature of the image processing apparatus according to the present invention is that a component ratio calculation for calculating a data component ratio of the target image data from the luminance data and the color difference data converted by the color space conversion means. Further comprising means,
The quantization coefficient selection means selects the quantization coefficient based on the data component ratio of the target image data calculated by the component ratio calculation means. Another feature of the image processing apparatus of the present invention is that the component ratio means calculates a ratio of at least one of data components of luminance data and color difference data to all data components of the target image data. I do.

According to another feature of the image processing apparatus of the present invention, the image input means inputs, together with the target image data, an attribute flag indicating an attribute of a region of an image related to the target image data, and The quantization coefficient selection means selects a quantization coefficient based on the attribute flag and the target image data subjected to color space conversion by the color space conversion means.

Another feature of the image processing apparatus of the present invention is that image input means for inputting an attribute flag indicating an attribute of an area of an image related to the target image data together with the target image data; Image attribute determining means for determining the attribute of the image area of M × N pixels based on an attribute flag indicating the attribute of the image area of M × N pixels of the input target image data; And a code for encoding the M × N pixel image data using the quantization coefficient selection means for selecting the quantization coefficient based on the determination result by And a conversion means.

Another feature of the image processing apparatus of the present invention is that the encoding means performs JPEG encoding. Another feature of the image processing apparatus of the present invention is that the image processing apparatus includes a plurality of quantization coefficients.

An image processing system according to the present invention is an image processing system in which a plurality of devices are communicably connected to each other, wherein at least one of the plurality of devices is any one of the above-described image processing devices. It has a function of a processing device.

Further, the image processing method of the present invention is an image processing method for encoding image data of an arbitrary image, the method comprising the steps of: A quantization coefficient selection step of selecting a quantization coefficient based on the target image data subjected to the color space conversion by the step; and encoding the image data using the quantization coefficient selected in the quantization coefficient selection step. Encoding step.

Another feature of the image processing method of the present invention is that the color space converting step converts the image data into luminance data and color difference data. According to another feature of the image processing method of the present invention, the quantization coefficient selection step includes an attribute flag indicating an attribute of a region of an image related to the image data input together with the image data, and the color space conversion step. And a quantization coefficient is selected based on the target image data subjected to the color space conversion according to (1).

Another feature of the image processing method of the present invention is an image processing method for encoding image data of an arbitrary image, wherein the image data is converted into luminance data and color difference data in a color space. A color space conversion step of converting, a component ratio calculation step of calculating a data component ratio of the image data from the luminance data and the color difference data obtained in the color space conversion step, and a component ratio calculation step. The image data is encoded using a quantization coefficient selection step of selecting a quantization coefficient based on a ratio of the data component of the image data, and a quantization coefficient selected in the quantization coefficient selection step. Encoding step.

Another feature of the image processing method of the present invention is an image processing method for encoding image data of an arbitrary image, wherein the image data is input together with the image data of M × N pixels. An image attribute determining step of determining an attribute of the M × N pixel image area based on an attribute flag indicating an attribute of the image area related to the image data; And a coding step of coding the M × N pixel image data using the quantization coefficient selected in the quantization coefficient selection step. And

Another feature of the image processing method of the present invention is that the above-mentioned encoding includes JPEG encoding.

A computer-readable recording medium according to the present invention is characterized in that a program for causing a computer to function as each of the above means is recorded. Another feature of the computer-readable recording medium of the present invention is that a program for causing a computer to execute the processing steps of the image processing method is recorded.

The program of the present invention causes a computer to function as each of the above means. Another feature of the program of the present invention is that the program causes a computer to execute the processing steps of the image processing method.

[0021]

Embodiments of the present invention will be described below with reference to the drawings. (First Embodiment) The present invention is applied to, for example, an image processing apparatus 100 as shown in FIG. The image processing apparatus 100 according to the present embodiment selects a quantization coefficient (quantization matrix) suitable for input image data according to the ratio of color components of the input image data when performing image compression processing on the input image data. With this configuration, image compression that minimizes image quality degradation due to image compression processing is realized. Hereinafter, the image processing apparatus 100 according to the present embodiment will be specifically described.

In FIG. 1, an image processing apparatus 100 switches between an input from an image scanner unit 120 and an input (image input system) from a page description language rendering unit 121 and outputs the same. A line buffer (compression block line buffer) 101 for accumulation, and an attribute flag encoding unit 102 for encoding attribute flag data from the line buffer 101
Determining unit 103 that determines the attribute (image attribute) of the input image based on the attribute flag data from line buffer 101
And an encoding unit 104 that encodes image data from the line buffer 101, and temporarily stores the attribute flag encoding unit 102 and the encoded data (compressed image data and compressed attribute flag data) obtained by the encoding unit 104. And a hard disk (HDD) 106 for storing the encoded data stored in the compression buffer 105.
And encoded data (compressed image data and compressed attribute flag data) corresponding to the image in the hard disk (HDD) 106 when the image data in the hard disk (HDD) 106 is printed out by the printer unit 112 or the like.
Buffer 107 for temporarily storing data, and compression buffer 1
07, an attribute flag decoding unit 108 for decoding the compressed attribute flag data accumulated in 07, and a compressed attribute flag decoding unit 1
A determination unit 109 for determining the attribute of the image to be processed from the attribute flag data obtained in step 08 and a decoding unit 110 for decoding the compressed image data stored in the compression buffer 107
And a line buffer (development block buffer) 111 for temporarily storing the image data processed by the decoding unit 110 and outputting it to the printer unit 112.

FIG. 2 is a block diagram of the encoding unit 104 shown in FIG.
2 shows an internal configuration of the decoding unit 110.
The encoding unit 104 includes a color space conversion unit 201, a color component ratio calculation unit 202, a quantization coefficient selection unit 203, a discrete cosine transform (DCT) unit 204, a quantization unit 205, and a variable length, as shown in FIG. An encoding (VLC) unit 206 is included. Also, the decoding unit 110 performs variable length decoding (VL
D) unit 207, inverse quantization unit 208, DCT inverse transform (ID
CT) unit 209 and a color space conversion unit 210.

First, in the encoding unit 104, the input image from the selector 130 is supplied to the color space conversion unit 201. The input image here is, for example, a color image signal and includes three colors of red (R), green (G), and blue (B), 256 colors.
It is a gradation signal (RGB image signal). Therefore, the color space conversion unit 201 converts the RGB image signal into a luminance color difference signal (YCbCr signal).

The color component ratio calculation unit 202 calculates the ratio of each color component of the luminance / color difference signal obtained by the color space conversion unit 201. The quantization coefficient selection unit 203 includes a color component ratio calculation unit 2
A quantization coefficient (quantization matrix) for quantizing the DCT coefficient obtained by the discrete cosine transform (DCT) unit 204 is selected based on the calculation result of the ratio of the color component obtained in step 02. The details of the color component ratio calculation unit 202 and the quantization coefficient selection unit 203 will be described later.

The discrete cosine transform (DCT) unit 204
For each of the luminance and chrominance signals obtained by the color space conversion unit 201, spatial frequency conversion (DCT
Conversion). The quantization unit 205 includes a quantization coefficient selection unit 2
The data amount of the target image data is reduced by quantizing the DCT coefficient obtained by the DCT transform unit 204 using the quantization coefficient (quantization matrix) selected in 03. The variable length coding (VLC) unit 206 further reduces the data amount of the target image data by performing the Huffman coding process on the quantized value obtained by the quantization unit 205.

As described above, the encoded data (compressed image data) obtained by the encoding unit 104 is stored in the hard disk 106 (or the compression buffer 105).

When decoding the compressed image data stored in the hard disk 106 (or the compression buffer 105), the decoding unit 110 performs variable length decoding (VLD).
The unit 207 reads out the target compressed image data from the hard disk 106 (or the compression buffer 105) and performs Huffman decoding (decoding). Inverse quantization unit 208
Returns the data after processing in the variable length decoding (VLD) unit 207 to a DCT coefficient value using an inverse quantization matrix corresponding to the encoding unit 104 set in advance.

The inverse DCT transform unit 209 includes an inverse quantization unit 20
By performing a DCT inverse transform on the DCT coefficient value obtained in step 8, a luminance / color difference signal is obtained. Color space conversion unit 21
“0” returns the luminance / color difference signal obtained by the inverse DCT transform unit 209 to an RGB image signal.

Therefore, the RGB image signal (color image signal) obtained by the color space conversion unit 210 of the decoding unit 110
Is printed out by the printer unit 112.

FIG. 3 shows an image processing apparatus 100 according to this embodiment.
FIG. 9 is a diagram for describing in detail a process of selecting a quantization coefficient (quantization matrix) according to FIG. First, the color space conversion unit 201 converts an RGB image signal of an input image (color image signal) supplied through the selector 130 into a luminance color difference signal (YCbCr signal). Color component ratio calculation unit 2
In step 02, the ratio of each color component of the target image data is calculated using the luminance / color difference signal obtained by the color space conversion unit 201.
As a specific method of calculating the ratio of each color component in the color component ratio calculation unit 202, the luminance component of the luminance / color difference signal is compared with the entire components of the original image data, and the luminance / color difference signal for the entire component is compared. Calculate the ratio of the luminance component.

The quantization coefficient selection unit 203 quantizes the DCT coefficient of the target image data based on the ratio of each color component of the target image data calculated by the color component ratio calculation unit 202.
In step 5, a quantization coefficient to be applied when quantization is selected. Specifically, when the ratio of the luminance component of the luminance / color difference signal to the total components calculated by the color component ratio calculation unit 202 is greater than 60%, the quantization coefficient selection unit 203 determines the quantization coefficient T1 shown in FIG. Is selected. On the other hand, the quantization coefficient selection unit 203 includes the color component ratio calculation unit 20
When the ratio of the luminance component of the luminance / chrominance signal to the total components calculated in 2 is 60% or less, a quantization coefficient effective for an image including a color component such as a quantization coefficient T2 shown in FIG. select. FIG. 5 will be described later. As described above, the quantization coefficient selection unit 203 sets in advance the threshold value and the quantization coefficient to be applied in accordance with the determination result using the threshold value, and sets each of the colors of the target image data obtained by the color component ratio calculation unit 202. The quantization coefficient is automatically determined based on the ratio of the components.

The threshold value set in the quantization coefficient selection unit 203, that is, the ratio of the luminance component of the luminance / chrominance signal to the entire components is not limited to 60%, and an arbitrary threshold value can be set. The number of quantization coefficients set in the quantization coefficient selection unit 203 selected based on the ratio of each color component of the target image data is not limited to one, and an arbitrary number of quantization coefficients can be set.

The quantization unit 205 converts the DCT of the target image data obtained by the color space conversion unit 201 into a luminance / chrominance signal, and the discrete cosine transform (DCT) unit 204 through a spatial frequency transform (DCT). The coefficient is quantized using the quantization coefficient selected by the quantization coefficient selection unit 203. Therefore, the encoding unit 104 can quantize the target image data with a quantization coefficient suitable for the ratio of each color component of the target image data (input image data).

Next, the operation of the image processing apparatus 100 shown in FIGS. 1 to 3 will be described. FIG. 4 is a flowchart illustrating the operation of the image processing apparatus 100.

First, the selector 130 switches the input from the image scanner unit 120 or the input from the page description language rendering unit 121. For example, the selector 130 switches to an input from the image scanner unit 120 when the image processing apparatus 100 functions as a copier, and the page description language rendering unit 121 when the image processing apparatus 100 functions as a printer. (S401, S402).

Here, the image scanner unit 120 has an arbitrary image area separation processing function, and generates, for example, attribute flag data for identifying pixels constituting a black character portion in a document image in pixel units. Is configured. Also,
The page description language rendering unit 121 generates a print image by interpreting the PDL command. At this time, the page description language rendering unit 121 refers to information indicating the type of the command, and, similarly to the image scanner unit 120, generates a pixel constituting a black character portion. Is configured to generate attribute flag data for identifying pixel by pixel.

Therefore, the image data 1001 and the attribute flag data 1003 obtained by the image scanner unit 120 or the image data 1002 and the attribute flag data 1004 obtained by the page description rendering unit 121 are supplied from the selector 130 to the line buffer 101.
Will be output via the

It should be noted that the attribute flag data is not limited to data for identifying pixels constituting a black character portion. For example, a photograph portion, a print portion, a color character portion, a thin line portion, a halftone dot portion, It is also possible to use multi-bit information indicating various attributes such as a vector graphics section as attribute flag data.

The color space conversion unit 201 converts the image data (RGB image signals) 1001 and 1003 supplied via the selector 130 and the line buffer 101 into a luminance / color difference signal (YCbCr signal) (S403). The color component ratio calculation unit 202 calculates the ratio of each color component of the target image data to the entire components of the original image data by using the luminance / color difference signals obtained by the color space conversion unit 201 (S4).
04).

The quantization coefficient selection unit 203 compares the preset threshold value with the ratio of each color component of the target image data obtained by the color component ratio calculation unit 202 to the total components (S405). As a result of the comparison in step S405, if the ratio of the color component of the target image data is equal to or less than the threshold (the ratio of the luminance component of the target image data is larger than the threshold), the quantization coefficient selection unit 203 T1 is selected (S406). On the other hand, the quantization coefficient selection unit 203
If the ratio of the color components of the target image data is larger than the threshold value (the ratio of the luminance components of the target image data is equal to or less than the threshold value) as a result of the comparison in step S405, the quantization coefficient T
2 is selected (S407).

The discrete cosine transform (D
The CT unit 204 performs spatial frequency conversion (DCT conversion) on the luminance / color difference signals output from the color space conversion unit 201 in units of 8 × 8 pixels. Further, the quantization unit 205 uses the quantization coefficient selected by the quantization coefficient selection unit 203 based on the ratio of the color component of the target image data, and obtains the target image obtained by the discrete cosine transform (DCT) unit 204. Quantize the DCT coefficients of the data. The variable-length coding (VLC) unit 206 performs variable-length coding on the target image data quantized by the quantization unit 205 and temporarily stores the compressed image data (encoded data) in the compression buffer 105. . Further, the attribute flag encoding unit 102 encodes the attribute flag data output from the line buffer 101 and generates compressed attribute flag data (encoded data).
The data is temporarily stored in the compression buffer 105 (S408).

Coded data (compressed image data and compression attribute flag data) stored in the compression buffer 105
Is stored in the hard disk 106 (S409).

For example, when an image stored in the hard disk 106 is printed out from the printer unit 112, the compressed image data and the compressed attribute flag data stored in the hard disk 106 are temporarily stored in the compression buffer 10
7 and stored. Attribute flag decoding unit 1
08 reads out the compressed attribute flag data from the compression buffer 107 and decodes it. Further, the decoding unit 110 reads out the compressed image data from the compression buffer 107 and decodes it by setting an inverse quantization coefficient (inverse quantization matrix) corresponding to the encoding unit 104. The determination unit 109
The attribute of the image to be processed is determined based on the attribute flag data after decoding obtained by the attribute flag decoding unit 108 (S410). The decoded image data is printed out from the printer unit 112 via the line buffer 111 (S411).

FIG. 5 is a diagram showing an example of a quantization matrix for DCT coefficients in units of 8 × 8 pixels selected by the quantization coefficient selection unit 203 and used by the quantization unit 205. FIG. 5A is not suitable for encoding an image containing a vivid color close to the primary color, that is, for example, when the luminance component of the target image data is larger than 60% of the entire component of the original image data. The selected quantization matrix (quantization coefficient) T1
It is. FIG. 5B is effective for an image containing a color component, that is, for example, a quantum selected when the luminance component of the target image data is 60% or less of the entire component of the original image data. Matrix (quantization coefficient) T2.

The quantization matrix can be set arbitrarily instead of T1 and T2. According to the present invention, when the input image is subjected to the image compression processing, the input image is quantized by changing the quantization matrix in accordance with each color component constituting the input image. You can do it.

In the above-described embodiment, the quantization coefficient selection unit 203 calculates the quantization coefficient suitable for the target image data based on the calculation result of the color component ratio obtained by the color component ratio calculation unit 202. (Quantization matrix) is selected, but the determination result of the attribute (image attribute) of the input image obtained by the determination unit 103 is
So that a quantization coefficient (quantization matrix) suitable for the target image data is selected based on the determination result of the attribute (image attribute) of the input image and the calculation result of the ratio of the color components. May be.

(Second Embodiment) Next, a second embodiment will be described. In the second embodiment, the image processing apparatus 100 shown in FIG. 1 performs encoding processing such as quantization within M × N pixels. That is, in the second embodiment, the image data of M × N pixels in the target image data is determined based on the ratio of the color components in the M × N pixels, the statistical value of the attribute flag data in the M × N pixels, and the like. Quantization is performed by selecting a quantization coefficient (quantization matrix) suitable for.

For example, the compressed block line buffer 10
In step 1, input image data is divided into tile images (block images) composed of M × N pixels and output. The encoding unit 104 and the attribute flag encoding unit 102 perform discrete cosine transform encoding of image data (JPEG encoding) and run-length encoding of attribute flag data for each block of M × N pixels.

Here, it is assumed that the block sizes "M" and "N" are multiples of the window size in the discrete cosine transform coding. For example, in JPEG encoding, the window size is set to 8 × 8 pixels and “M”
= “N” = 32. In this case, in JPEG encoding, a block of 32 × 32 pixels is further divided into 8 × 8 blocks.
Encoding is performed in units of pixel blocks.

Therefore, the encoding unit 104 converts the 16 8 × 8 pixel windows included in the 32 × 32 pixel block image from the line buffer 101 into
A so-called DCT process is performed to quantize. The quantization coefficient (quantization matrix) used at this time can be switched and set for each block of M × N pixels, and this switching signal is input to the attribute flag encoding unit 102.

More specifically, 3 corresponding to the above image data
The determination unit 10 refers to the attribute flag data of 2 × 32 pixels.
3, the attribute of the block of M × N pixels (for example, character area,
A determination process for determining a photographic region) is performed, a quantization coefficient selection signal is generated and sent to the encoding unit 104, and the quantization coefficient selection unit 203 selects a quantization coefficient suitable for M × N pixel image data. (Quantization matrix) is selected.

The attribute flag data is attached to each pixel. However, since the encoding method in the M × N pixel tile is fixed as in the present invention, the attribute flag data in the tile is attribute flag encoded. That is, it is necessary to determine the attribute representative of the tile by performing the analysis in the unit 102. For example,
When a pixel having a character attribute is included in an image of M × N pixels, the image of M × N pixels may be determined and determined to be an image of a character attribute, or an image of M × N pixels may be determined. The attributes of all the pixels in the image may be added for each attribute, and the attribute indicating the maximum value may be an image attribute of M × N pixels.

In the second embodiment, M × M
The quantization coefficient is selected for each image of M × N pixels based on the image attribute of N pixels.
As in the image processing apparatus 100 shown in FIG. 3, the color component ratio calculation unit 202 calculates the ratio (M
A ratio of the luminance signal component of the image of × N pixels to the whole component is calculated, and a quantization coefficient (quantization matrix) suitable for the image data of M × N pixels is calculated by the quantization coefficient selection unit 203 based on the calculation result. ) May be selected.

(Other Embodiments of the Present Invention) The image processing apparatus 100 according to the first and second embodiments is, for example, a computer, an image input apparatus, and an image output apparatus as shown in FIG. It is also possible to connect and use. In this case, the computer and the image input device function as an image input system for inputting an image to be encoded, and the image output device functions as an image output system for decoding and printing out the encoded image. .

Another object of the present invention is to supply a recording medium storing program codes of software for realizing the functions of the host and the terminal of the first and second embodiments to a system or an apparatus, and to supply the recording medium to the system or the apparatus. It is needless to say that the present invention can also be achieved by a computer (CPU or MPU) reading and executing the program code stored in the recording medium.

In this case, the program code of the software implements the functions of the first and second embodiments described above, and the program code itself and means for supplying the program code to the computer, For example, a recording medium storing such a program code constitutes the present invention. As a recording medium for storing such a program code, for example, a flexible disk, hard disk, optical disk, magneto-optical disk, C
D-ROM, magnetic tape, nonvolatile memory card, R
OM or the like can be used.

The computer executes the supplied program code to execute the first and second programs.
Not only realizes the functions of the first embodiment, but also executes
Needless to say, even when the functions of the above-described embodiments are realized in cooperation with an (operating system) or other application software, such program codes are included in the embodiments of the present invention.

Further, after the supplied program code is stored in a memory provided in a function expansion board of the computer or a function expansion unit connected to the computer, the function expansion board or the function expansion unit is specified based on the instruction of the program code. It is needless to say that the present invention also includes a case where the CPU or the like provided in the first embodiment performs part or all of the actual processing, and the processing realizes the functions of the above-described embodiments.

FIG. 7 shows a function 700 of the computer. For example, the image processing apparatus 100 has the computer function 700 shown in FIG. 7, and the operations of the first and second embodiments are performed by the CPU 701.

As shown in FIG. 7, the computer function 700 includes a CPU 701, a ROM 702, and a RAM 7
03, a keyboard controller (KBC) 705 of a keyboard (KB) 709, and a CRT controller (CR) of a CRT display (CRT) 710 as a display unit.
TC) 706, a hard disk (HD) 711 and a disk controller (DKC) 707 of a flexible disk (FD) 712, and a network interface card (NIC) 708 communicably connected to each other via a system bus 704. And

The CPU 701 has the ROM 702 or H
Software stored in D711 or FD71
By executing the software supplied from 2, the respective components connected to the system bus 704 are comprehensively controlled. That is, the CPU 701 executes the processing program according to the processing sequence shown in FIG.
02, or the HD 711 or the FD 712, the control for realizing the operations in the first and second embodiments is performed.

The RAM 703 functions as a main memory or a work area of the CPU 701. KBC705
Controls an instruction input from the KB 709 or a pointing device (not shown). CRTC 706 is
The display of the RT 710 is controlled. The DKC 707 includes a boot program, various applications, editing files,
It controls access to the HD 711 and the FD 712 that store a user file, a network management program, and the above-described processing programs in the first and second embodiments. The NIC 708 bidirectionally exchanges data with other devices on the network 713 (computers, image input devices, image output devices, and the like as shown in FIG. 6).

[0064]

As described above, according to the present invention, when subject image data (such as a color image signal) is subjected to image compression processing, the input subject image data is subjected to color space conversion.
A quantization coefficient is selected based on the target image data subjected to the color space conversion, and the input target image data is encoded using the selected quantization coefficient. With this, it is possible to select a quantization coefficient corresponding to the color component of the target image data according to the input target image data, and encode the target image data using the selected quantization coefficient. Image quality deterioration due to processing can be reduced.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of an image processing apparatus to which the present invention has been applied.

FIG. 2 is a diagram illustrating a configuration of an encoding unit and a decoding unit of the image processing apparatus.

FIG. 3 is a diagram illustrating a quantization coefficient selection process performed by the image processing apparatus.

FIG. 4 is a flowchart illustrating an operation of the image processing apparatus.

FIG. 5 is a diagram illustrating an example of a quantization matrix selected in a quantization coefficient selection process.

FIG. 6 is a diagram for explaining a connection example of the image processing apparatus.

FIG. 7 is a block diagram illustrating an example of a computer function of the image processing apparatus.

[Explanation of symbols]

 REFERENCE SIGNS LIST 100 Image processing device 101 Line buffer 102 Attribute flag encoding unit 103 Judgment unit 104 Encoding unit 105 Compression buffer 106 Hard disk 107 Compression buffer 108 Attribute flag decoding unit 109 Judgment unit 110 Decoding unit 111 Line buffer 112 Printer unit 120 Image scanner Unit 121 page description language rendering unit 130 selector 201 color space conversion unit 202 color component ratio calculation unit 203 quantization coefficient selection unit 204 discrete cosine transform (DCT) unit 205 quantization unit

──────────────────────────────────────────────────の Continued on the front page (51) Int.Cl. ⁷ Identification symbol FI Theme coat ゛ (Reference) H04N 1/46 H04N 1/40 D 5J064 1/60 F 7/30 1/46 Z F Term (Reference) 5B057 AA11 BA01 BA02 BA29 CE17 CE18 CG04 CG05 CH08 CH18 DA08 DA17 DB02 DB06 DC01 DC25 5C059 KK01 MA00 MA23 MC14 MC38 ME02 PP01 PP15 PP16 PP18 SS12 SS20 SS28 TA47 TB04 TB08 TC00 TC24 TD12 UA02 UA05 UA32 UA39 5C06PP PPPP PPPP PPPP PP68 PQ08 PQ20 RR21 TT02 5C078 AA09 BA21 BA23 BA57 CA00 DA00 DA01 DB07 5C079 HB01 HB04 HB11 LA06 LA27 LA31 LB00 NA02 PA03 5J064 AA01 BA09 BA16 BC16 BC25 BD01

Claims (19)

[Claims] 1. An image input unit for inputting target image data, a color space conversion unit for converting the target image data input by the image input unit into a color space, and an object color space converted by the color space conversion unit Coding the target image data input by the image input means using the quantization coefficient selection means for selecting the quantization coefficient based on the image data, and the quantization coefficient selected by the quantization coefficient selection means; An image processing apparatus comprising: an encoding unit that performs encoding. 2. The image processing apparatus according to claim 1, wherein the color space conversion means converts the target image data input by the image input means into luminance data and color difference data. 3. The apparatus according to claim 1, further comprising: a component ratio calculating unit configured to calculate a ratio of a data component of the target image data from the luminance data and the color difference data converted by the color space converting unit. 3. The image processing apparatus according to claim 2, wherein the quantization coefficient is selected based on a ratio of data components of the target image data calculated by the component ratio calculation unit. 4. The image processing apparatus according to claim 3, wherein said component ratio means calculates a ratio of at least one of the luminance data and the color difference data to all data components of the target image data. . 5. The image input unit inputs, together with the target image data, an attribute flag indicating an attribute of a region of an image related to the target image data, wherein the quantization coefficient selecting unit includes the attribute flag and the color space. 2. The image processing apparatus according to claim 1, wherein a quantization coefficient is selected based on the target image data subjected to the color space conversion by the conversion unit. 6. An image input means for inputting an attribute flag indicating an attribute of an area of an image relating to the target image data together with the target image data, and M of the target image data input by the image input means.
Image attribute determining means for determining the attribute of the image area of M × N pixels based on an attribute flag indicating the attribute of the image area of × N pixels; And a coding means for coding the image data of the M × N pixels by using the quantization coefficient selected by the quantization coefficient selection means. Image processing apparatus. 7. The image processing apparatus according to claim 1, wherein said encoding means performs JPEG encoding. 8. The image processing apparatus according to claim 1, comprising a plurality of quantization coefficients. 9. An image processing system in which a plurality of devices are communicably connected to each other, wherein at least one of the plurality of devices is the image according to any one of claims 1 to 8. An image processing system having a function of a processing device. 10. An image processing method for encoding image data of an arbitrary image, comprising: a color space conversion step of converting the image data into a color space; and an object subjected to the color space conversion by the color space conversion step. A quantization coefficient selection step of selecting a quantization coefficient based on the image data; and an encoding step of encoding the image data using the quantization coefficient selected in the quantization coefficient selection step. An image processing method characterized by the following. 11. The image processing method according to claim 10, wherein the color space conversion step converts the image data into luminance data and color difference data. 12. The quantization coefficient selection step includes the steps of: providing an attribute flag indicating an attribute of an area of an image related to the image data input together with the image data; and target image data subjected to color space conversion by the color space conversion step. 2. The method according to claim 1, wherein the quantization coefficient is selected based on the selected coefficient.
0. The image processing method according to 0. 13. An image processing method for encoding image data of an arbitrary image, comprising: a color space conversion step of performing a color space conversion of the image data into luminance data and color difference data; From the luminance data and the color difference data obtained by the above, based on the component ratio calculation step of calculating the ratio of the data components of the image data, based on the ratio of the data components of the image data calculated by the component ratio calculation step, Image processing comprising: a quantization coefficient selection step of selecting a quantization coefficient; and an encoding step of encoding the image data using the quantization coefficient selected in the quantization coefficient selection step. Method. 14. An image processing method for encoding image data of an arbitrary image, comprising: an attribute flag indicating an attribute of a region of an image related to the image data input together with the image data of M × N pixels Based on the image attribute determining step of determining the attribute of the area of the image of M × N pixels, based on the determination result by the image attribute determining step,
A quantization coefficient selection step of selecting a quantization coefficient; and an encoding step of encoding the image data of the M × N pixels using the quantization coefficient selected in the quantization coefficient selection step. Characteristic image processing method. 15. The image processing method according to claim 10, wherein the encoding includes JPEG encoding. 16. A computer-readable recording medium on which a program for causing a computer to function as each of the means according to claim 1 is recorded. 17. A computer-readable recording medium on which a program for causing a computer to execute the processing steps of the image processing method according to claim 10 is recorded. 18. A program for causing a computer to function as each means according to claim 1. Description: 19. A program for causing a computer to execute the processing steps of the image processing method according to claim 10. Description: