CN103778900A - Image processing method and system - Google Patents
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- CN103778900A CN103778900A CN201210406037.5A CN201210406037A CN103778900A CN 103778900 A CN103778900 A CN 103778900A CN 201210406037 A CN201210406037 A CN 201210406037A CN 103778900 A CN103778900 A CN 103778900A
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Abstract
The invention discloses an image processing method and a system, so as to improve a dynamic range and permeability of an image. The image processing method provided by the invention comprises steps: initial brightness of each pixel of the image is used to determine a gray histogram of the image; according to the gray histogram, a method of combining equalization and equal proportion is used for determining the gray mapping relationship of the image; and according to the gray mapping relationship of the image, the output brightness of each pixel of the image is determined to obtain the output image.
Description
Technical field
The present invention relates to image processing field, relate in particular to a kind of image processing method and image processing apparatus.
Background technology
At present, some pictures that we obtain by video camera or camera, due to photographed scene difference, can obtain different image effects, for example can obtain good image effect for the shooting of fine day scene, but for the shooting of the scene such as rainy day, greasy weather, the image of often taking is got confused, or partially dark, details is abundant not, integral image permeability is inadequate, and therefore, the dynamic range that how can improve adaptively image obtains the gordian technique that well arranged informative image is image processing.
Current existing technology is generally to realize the dynamic range lifting of image by gamma conversion, curvilinear transformation, histogram equalization or regulation etc., but these methods cannot well be accomplished self-adaptation, and dynamic range and permeability are met the demands simultaneously.
Summary of the invention
The embodiment of the present invention provides a kind of image processing method and system, in order to improve dynamic range and the permeability of image.
A kind of image processing method that the embodiment of the present invention provides, comprising:
Utilize the original intensity of each pixel of image, determine the grey level histogram of this image;
According to described grey level histogram, the method for utilizing equalization and geometric ratio to combine, the grey scale mapping relation of computed image;
Utilize the grey scale mapping relation of image, thereby determine that the output brightness of each pixel of image obtains output image.
A kind of image processing system that the embodiment of the present invention provides, comprising:
Grey level histogram determining unit, for utilizing the original intensity of each pixel of image, determines the grey level histogram of this image block;
Grey scale mapping is related to determining unit, and for according to described grey level histogram, the method for utilizing equalization and geometric ratio to combine, determines the grey scale mapping relation of image;
Output image determining unit, for utilizing the grey scale mapping relation of image, thereby determines that the output brightness of image obtains output image.
A kind of image processing method and system that the embodiment of the present invention provides, according to the original intensity of image, the method of utilizing equalization and geometric ratio to combine, calculate the grey scale mapping relation of image and utilize this grey scale mapping relation to determine the output brightness of image according to the original intensity of each pixel of image, improved dynamic range and the permeability of image.
Accompanying drawing explanation
The main schematic flow sheet of a kind of image processing method that Fig. 1 provides for the embodiment of the present invention;
The detailed process schematic diagram of a kind of image processing method that Fig. 2 provides for the embodiment of the present invention;
Fig. 3 is the schematic diagram to mapping relations according to histogram calculation 7 described in the embodiment of the present invention;
Fig. 4 goes out gray scale and draws high the schematic diagram of curve by 7 pairs of mapping relations interpolation described in the embodiment of the present invention;
The structural representation of a kind of image processing system that Fig. 5 provides for the embodiment of the present invention.
Embodiment
The embodiment of the present invention provides a kind of image processing method and system, in order to improve dynamic range and the permeability of image.
A kind of image processing method that the embodiment of the present invention provides, referring to Fig. 1, the method comprises:
Preferably, the described original intensity that utilizes each pixel of image, determine and comprise the grey level histogram of this image:
Utilize the original intensity of each pixel of image, the original intensity of each pixel of image is carried out to exponential transform, the brightness after the exponential transform of each pixel of output image; For example, if image is gray-scale map, directly use original intensity to determine the grey level histogram of this gray-scale map; If image is coloured image, calculate the original intensity of each pixel, determine the grey level histogram of this coloured image according to this original intensity;
According to the brightness after the exponential transform of each pixel of image, determine the grey level histogram of this image.
Preferably, utilize the original intensity of each pixel of image, the original intensity of each pixel of image is carried out to γ exponential transform, the brightness after the γ exponential transform of each pixel of output image
Preferably, the brightness after the described exponential transform that utilizes image, the grey level histogram of statistical picture, comprising:
Brightness after exponential transform is divided to gray level, and multiple gray levels are merged into a gray-scale statistical interval;
According to described gray-scale statistical interval, determine the grey level histogram of image.
Preferably, described according to described grey level histogram, determine and comprise the grey scale mapping relation of image:
The method that adopts equalization and geometric ratio to combine according to described grey level histogram, successively calculates multipair mapping relations;
According to multipair mapping relations and minimum gray level and high grade grey level, utilize interpolation calculation to go out the grey scale mapping relation of each image.
Preferably, the algorithm that adopts equalization and geometric ratio to combine according to described grey level histogram, successively calculates seven pairs of mapping relations.
Preferably, described method of interpolation comprises: linear interpolation method, B spline method or Bezier method of interpolation.
Preferably, described method of interpolation is linear interpolation method.
Below in conjunction with accompanying drawing and concrete preferred embodiment, the present invention is described in detail, in this preferred embodiment, supposes that needing image to be processed be coloured image.It should be noted that, this specific embodiment is for technical scheme of the present invention is described, but does not limit technical scheme of the present invention.
Referring to Fig. 2, the process flow diagram of the image processing method providing for the embodiment of the present invention, its method comprises:
Step 201, the original intensity of each pixel of computed image;
Particularly, being calculated as of original intensity:
Y=0.299R+0.587G+0.114B；
Wherein, Y is original intensity, and R, G, B are three color components;
Step 202, carries out γ exponential transform by original intensity, obtains the brightness after the exponential transform of each pixel of image; Be specially:
Y＝(Y/Y
max)
γ*Y
max；
Wherein, Y ' is the brightness after exponential transform, Y
maxfor the not corresponding brightness of maximum gray scale, γ is adjustable factors, and span is that the dark portion of the larger image of 0 ~ 1, γ is brighter, and in this programme, giving tacit consent to value is 1/1.8.
Step 203, utilizes the brightness after the exponential transform of each pixel of image, determines the grey level histogram of this image;
Particularly, the brightness after the exponential transform of image is divided to gray level, and multiple gray levels are merged into a gray-scale statistical interval, to reduce the histogrammic resource of depositing; According to described gray-scale statistical interval, determine the grey level histogram of image.
Step 204, according to described grey level histogram, the method for utilizing equalization and geometric ratio to combine, determines the grey scale mapping relation of image;
Particularly, for the histogram distribution situation of image, the algorithm that adopts equalization and geometric ratio to combine, successively finds out 7 pairs of mapping relations, and as shown in Figure 3, first finding out gray level is C
0luminance point, then to find out gray level be C
00and C
01luminance point, next finding out gray level is C
000, C
001, C
010, C
011luminance point; Suppose that histogrammic minimal gray level is 0, maximum gray scale is Y
max, first find out central point A according to equalization
0, guarantee that in image-region, brightness value is A
0left and right (be that brightness is greater than A
0be less than A
0) number of pixels on both sides is suitable:
find out central point B according to geometric ratio again
0: B
0=0+ (1-α) Y
max, wherein α is adjustable factors, then the C of β after being synthesized in proportion
0=B
0+ β * (A
0-B
0); In like manner, with minimal gray level 0, maximum gray scale C
0find out A
00, B
00, then obtain C
00, with minimal gray level C
0, maximum gray scale Y
maxobtain C
01, with minimal gray level 0 maximum gray scale C
00obtain C
000..., with minimal gray level C
01maximum gray scale Y
maxobtain C
011; Consider the resource problem that on-site programmable gate array FPGA is realized, according to found out 7 pairs of relations, add 0 and Y
max, by the mapping relations interpolation of all the other gray levels out; Draw high curve with regard to the gray scale that has obtained this image block like this, represent with function P (Y ') at this, wherein α and β are adjustable factors, span is between 0 ~ 1.0, it is larger that acquiescence is all got 0.5, α, and it is higher that brightness is afterwards drawn high through gray scale in this region, β is larger, and this region is higher through contrast after drawing high;
Above 7 pairs of relations are such, and above 7 pairs of relations are such, C
000->Y
max/ 8; C
00->2*Y
max/ 8; C
001->3*Y
max/ 8; C
0->4*Y
max/ 8; C
010->5*Y
max/ 8; C
01->6*Y
max/ 8; C
011->7*Y
max/ 8; Adopt linear interpolation method or B spline method or Bezier method of interpolation by the corresponding relation interpolation of all the other gray levels out, the present embodiment adopts linear interpolation method, as shown in Figure 4;
Step 205, according to this grey scale mapping relation, determines the output brightness of each pixel of image;
Particularly, be related to that according to grey scale mapping P (Y ') output brightness calculates in the following way:
Y "=P (Y '); Wherein, Y " be current pixel point output brightness, the brightness after index variation that Y ' is current pixel point;
Step 206, according to the original intensity of each pixel, output brightness and priming color channel value, determines the output Color Channel value of each pixel, thereby obtains output image;
Particularly, output Color Channel value is calculated in the following way:
C "=C*Y "/Y; Wherein C " expression output Color Channel value (R ", G ", B "), C represents priming color channel value (R, G, B); Thereby export the output image of whole colour.
Referring to Fig. 5, a kind of image processing system that the embodiment of the present invention provides, comprising:
Grey level histogram determining unit Z101, for utilizing the original intensity of each pixel of image, determines the grey level histogram of this image; Wherein, in the present embodiment, the original intensity of this coloured image calculates according to the priming color channel value of this coloured image;
Grey scale mapping is related to determining unit Z102, and for according to described grey level histogram, the method for utilizing equalization and geometric ratio to combine, determines the grey scale mapping relation of image
Output image determining unit Z103, for utilizing grey scale mapping relation, determines the output brightness of each pixel of image, thereby obtains output image; Wherein, in the present embodiment, the output image of this coloured image, obtains output Color Channel value according to the original intensity of this coloured image, output brightness and priming color channel value, and then the output image obtaining.
Preferably, described grey level histogram determining unit Z102, comprising:
Original intensity exponential transform unit, for utilizing the original intensity of each pixel of image, carries out exponential transform by the original intensity of each pixel of image, the brightness after the exponential transform of each pixel of output image;
Grey level histogram is determined subelement, for according to the brightness after the exponential transform of each pixel of image, determines the grey level histogram of this image.
Preferably, the original intensity of described each pixel of original intensity exponential transform unit by using image, carries out γ exponential transform by the original intensity of each pixel of image, the brightness after the γ exponential transform of each pixel of output image
Preferably, described grey level histogram is determined subelement, specifically for:
Brightness after image exponential transform is divided to gray level, and multiple gray levels are merged into a gray-scale statistical interval;
According to described gray-scale statistical interval, determine the grey level histogram of image.
Preferably, described grey scale mapping is related to determining unit Z103, specifically for:
The method that adopts equalization and geometric ratio to combine according to described grey level histogram, successively calculates multipair mapping relations;
According to multipair mapping relations and minimum gray level and high grade grey level, utilize the publish picture grey scale mapping relation of picture of interpolation calculation.
Preferably, described grey scale mapping is related to the method that determining unit Z103 adopts equalization and geometric ratio to combine according to described grey level histogram, successively calculates seven pairs of mapping relations.
Preferably, described grey scale mapping is related to that determining unit Z103 is according to multipair mapping relations and minimum gray level and high grade grey level, when the grey scale mapping of utilizing interpolation calculation to go out each image block is related to, described method of interpolation comprises: linear interpolation method, B spline method or Bezier method of interpolation.
Preferably, described grey scale mapping is related to that determining unit Z103, according to multipair mapping relations and minimum gray level and high grade grey level, utilizes linear interpolation method to calculate the grey scale mapping relation of image.
It should be noted that, the image of if desired processing is gray-scale map, only need to perform step 202 to step 205, just can obtain output image; Accordingly, in grey level histogram determining unit, directly determine grey level histogram according to the original intensity value of each pixel of gray-scale map; In output image determining unit, according to the output brightness obtaining, directly obtain output image.
In sum, a kind of image processing method and system that the embodiment of the present invention provides, according to the original intensity of image, the method of utilizing equalization and geometric ratio to combine, calculate the grey scale mapping curve of image, obtain the output brightness of image according to grey scale mapping curve, improved dynamic range and the permeability of image.
Those skilled in the art should understand, embodiments of the invention can be provided as method, system or computer program.Therefore, the present invention can adopt complete hardware implementation example, completely implement software example or the form in conjunction with the embodiment of software and hardware aspect.And the present invention can adopt the form at one or more upper computer programs of implementing of computer-usable storage medium (including but not limited to magnetic disk memory and optical memory etc.) that wherein include computer usable program code.
The present invention is with reference to describing according to process flow diagram and/or the block scheme of the method for the embodiment of the present invention, equipment (system) and computer program.Should understand can be by the flow process in each flow process in computer program instructions realization flow figure and/or block scheme and/or square frame and process flow diagram and/or block scheme and/or the combination of square frame.Can provide these computer program instructions to the processor of multi-purpose computer, special purpose computer, Embedded Processor or other programmable data processing device to produce a machine, the instruction that makes to carry out by the processor of computing machine or other programmable data processing device produces the device for realizing the function of specifying at flow process of process flow diagram or multiple flow process and/or square frame of block scheme or multiple square frame.
These computer program instructions also can be stored in energy vectoring computer or the computer-readable memory of other programmable data processing device with ad hoc fashion work, the instruction that makes to be stored in this computer-readable memory produces the manufacture that comprises command device, and this command device is realized the function of specifying in flow process of process flow diagram or multiple flow process and/or square frame of block scheme or multiple square frame.
These computer program instructions also can be loaded in computing machine or other programmable data processing device, make to carry out sequence of operations step to produce computer implemented processing on computing machine or other programmable devices, thereby the instruction of carrying out is provided for realizing the step of the function of specifying in flow process of process flow diagram or multiple flow process and/or square frame of block scheme or multiple square frame on computing machine or other programmable devices.
Obviously, those skilled in the art can carry out various changes and modification and not depart from the spirit and scope of the present invention the present invention.Like this, if within of the present invention these are revised and modification belongs to the scope of the claims in the present invention and equivalent technologies thereof, the present invention is also intended to comprise these changes and modification interior.
Claims (16)
1. an image processing method, is characterized in that, the method comprises:
Utilize the original intensity of each pixel of image, determine the grey level histogram of this image;
According to described grey level histogram, the method for utilizing equalization and geometric ratio to combine, determines the grey scale mapping relation of image;
Utilize the grey scale mapping relation of image, thereby determine that according to the original intensity of each pixel of image the output brightness of each pixel of image obtains output image.
2. image processing method according to claim 1, is characterized in that, the described original intensity that utilizes each pixel of image is determined and comprised the grey level histogram of this image:
Utilize the original intensity of each pixel of image, the original intensity of each pixel of image is carried out to exponential transform, the brightness after the exponential transform of each pixel of output image;
According to the brightness after the exponential transform of each pixel of image, determine the grey level histogram of this image.
3. image processing method according to claim 2, is characterized in that, utilizes the original intensity of each pixel of image, and the original intensity of each pixel of image is carried out to γ exponential transform, the brightness after the γ exponential transform of each pixel of output image.
4. image processing method according to claim 2, is characterized in that, the brightness after the described exponential transform that utilizes image, and the grey level histogram of statistical picture, comprising:
Brightness after exponential transform is divided to gray level, and multiple gray levels are merged into a gray-scale statistical interval;
According to described gray-scale statistical interval, determine the grey level histogram of image.
5. image processing method according to claim 2, is characterized in that, described according to described grey level histogram, determines the grey scale mapping relation of image, comprising:
The method that adopts equalization and geometric ratio to combine according to described grey level histogram, successively calculates multipair mapping relations;
According to multipair mapping relations and minimum gray level and high grade grey level, utilize interpolation calculation to go out the grey scale mapping relation of each gray level.
6. image processing method according to claim 5, is characterized in that, the algorithm that adopts equalization and geometric ratio to combine according to described grey level histogram, successively calculates seven pairs of mapping relations.
7. image processing method according to claim 5, is characterized in that, described method of interpolation comprises: linear interpolation method, B spline method or Bezier method of interpolation.
8. image processing method according to claim 5, is characterized in that, described method of interpolation is linear interpolation method.
9. an image processing system, is characterized in that, this system comprises:
Grey level histogram determining unit, for utilizing the original intensity of each pixel of image, determines the grey level histogram of this image block;
Grey scale mapping is related to determining unit, and for according to described grey level histogram, the method for utilizing equalization and geometric ratio to combine, determines the grey scale mapping relation of image.
Output image determining unit, for utilizing the grey scale mapping relation of image, determines the output brightness of each pixel of image, thereby obtains output image.
10. image processing system according to claim 9, is characterized in that, described grey level histogram determining unit, comprising:
Original intensity exponential transform unit, for utilizing the original intensity of each pixel of image, carries out exponential transform by the original intensity of each pixel of image, the brightness after the exponential transform of each pixel of output image;
Grey level histogram is determined subelement, for according to the brightness after the exponential transform of each pixel of image, determines the grey level histogram of this image.
11. image processing systems according to claim 10, it is characterized in that, the original intensity of described each pixel of original intensity exponential transform unit by using image, the original intensity of each pixel of image is carried out to γ exponential transform, the brightness after the γ exponential transform of each pixel of output image.
12. image processing systems according to claim 10, is characterized in that, described grey level histogram is determined subelement, specifically for:
Brightness after image exponential transform is divided to gray level, and multiple gray levels are merged into a gray-scale statistical interval;
According to described gray-scale statistical interval, determine the grey level histogram of image.
13. image processing systems according to claim 10, is characterized in that, described grey scale mapping is related to determining unit, specifically for:
The method that adopts equalization and geometric ratio to combine according to described grey level histogram, successively calculates multipair mapping relations;
According to multipair mapping relations and minimum gray level and high grade grey level, utilize the publish picture grey scale mapping relation of picture of interpolation calculation.
14. image processing systems according to claim 10, is characterized in that, described grey scale mapping is related to the method that determining unit adopts equalization and geometric ratio to combine according to described grey level histogram, successively calculates seven pairs of mapping relations.
15. image processing systems according to claim 13, it is characterized in that, described grey scale mapping is related to that determining unit is according to multipair mapping relations and minimum gray level and high grade grey level, when the grey scale mapping of utilizing interpolation calculation to go out each image block is related to, described method of interpolation comprises: linear interpolation method, B spline method or Bezier method of interpolation.
16. image processing systems according to claim 15, is characterized in that, described grey scale mapping is related to that determining unit, according to multipair mapping relations and minimum gray level and high grade grey level, utilizes linear interpolation method to calculate the grey scale mapping relation of image.
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