This repo is to implement color adjustment algorithm based on colorchecker.
The main idea of the algorithm is as follows: input a picture with a colorchecker, linearize the input colorchecker colors, and then use the color correction matrix(CCM) to linearly transform the former result to minimize the distance from the standard colorchecker colors. The goal of optimization is the ccm matrix.
After the ccm matrix is calculated, you can enter the picture for correction. The input picture is linearized, then multiplied by the ccm matrix, and then inversely linearized. Note that the rules for linearization and delinearization may be different.
Several linearization mechanisms such as gamma, sgrb, and polynomial are now supported.
The program has other options, such as color distance, optimization initial value. You can view the comments of the program.
The program is different from the Imatest software in terms of linearization and optimization initialization. The results of the program are compared with the results of Imatest, and most of them are consistent, especially the calculation results of the ccm matrix. But some results are quite different.
You can test with the 'test.py' file. The input colorchecker colors is got from Imatest software. The 'input1.png' test file is from http://cvil.eecs.yorku.ca/projects/public_html/sRGB_WB_correction/dataset.html, and 'input2.png' test file is from https://www2.cs.sfu.ca/~colour/data/shi_gehler/.
There will be more functions in branch v2.
- [x] weights
- [x] color space
- [x] new linearize class
- [x] accept customerized colorchecker
- [x] new ccm matrix
- [x] new distance function
- [x] rgb or bgr (determined: only rgb)
Future functions:
- [ ] value linearization functions (discard)
- [x] value optimization
- [ ] auto gamma (discard)
- [ ] auto optimization (discard)
- [ ] average RGB CS density, including relative detection
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ccm color calibration
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py:26个
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2023-02-05
16:01:58
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ccm color calibration
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ccm color calibration (235个子文件)
test.cpp 3KB
colorspace.h 13KB
distance.h 6KB
color.h 4KB
utils.h 3KB
io.h 2KB
operations.h 1KB
1414_Rods_and_Cones.jpg 646KB
1414_Rods_and_Cones.jpg 646KB
4_A7.jpg 261KB
2_A7.jpg 222KB
2_A6.jpg 216KB
2_A2.jpg 215KB
2_A3.jpg 211KB
2_A4.jpg 208KB
4_A6.jpg 199KB
4_A3.jpg 178KB
2_A1.jpg 172KB
3_A7.jpg 157KB
Deuteranopia_sight.jpg 151KB
Deuteranopia_sight.jpg 151KB
4_A2.jpg 145KB
4_A1.jpg 143KB
2_A5.jpg 139KB
1_A7.jpg 124KB
1_A4.jpg 122KB
1_A3.jpg 122KB
1_A2.jpg 122KB
1_A1.jpg 121KB
1_A6.jpg 120KB
3_A6.jpg 118KB
aa1_A6.jpg 116KB
4_A5.jpg 115KB
aa1_A7.jpg 113KB
aa1_A1.jpg 109KB
4_A4.jpg 108KB
1_A5.jpg 105KB
3_A2.jpg 103KB
aa1_A4.jpg 102KB
2.jpg 101KB
aa1_A3.jpg 100KB
3_A3.jpg 99KB
aa1_A5.jpg 98KB
3_A1.jpg 96KB
aa1_A2.jpg 96KB
3_A4.jpg 94KB
4.jpg 77KB
3_A5.jpg 76KB
1.jpg 58KB
3.jpg 53KB
Algorithm.md 22KB
算法介绍.md 19KB
ColorSpace.md 13KB
背景知识3—色彩空间.md 12KB
色彩空间.md 12KB
背景知识2—视觉.md 10KB
背景知识1—光谱和光源.md 8KB
背景知识4—色彩校正.md 8KB
Linearization.md 6KB
线性化.md 5KB
CCM.md 5KB
CCM矩阵.md 4KB
Miscellaneous.md 3KB
其他.md 3KB
README.md 2KB
objectdb 420B
背景知识3—色彩空间.pdf 9.88MB
算法介绍.pdf 2MB
Algorithm.pdf 1.84MB
背景知识2—视觉.pdf 1.28MB
色彩空间.pdf 621KB
Color Space.pdf 482KB
背景知识4—色彩校正.pdf 405KB
背景知识1—光谱和光源.pdf 365KB
其他.pdf 317KB
线性化.pdf 298KB
CCM矩阵.pdf 272KB
Miscellaneous.pdf 229KB
CCM.pdf 196KB
Linearization.pdf 196KB
image-20200530152641702.png 5.02MB
image-20200530152641702.png 5.02MB
input3_1.png 4.68MB
input3_5.png 4.67MB
input3_3.png 4.65MB
input3_4.png 4.64MB
input3_2.png 4.12MB
input2_2.png 4.09MB
input2_1.png 3.86MB
input2.png 3.7MB
image-20200530152735050.png 2.89MB
image-20200530152735050.png 2.89MB
input3.png 2.65MB
input1_A7.png 257KB
image-20200701165718350.png 257KB
image-20200701165718350.png 257KB
input1_A6.png 255KB
input1_A4.png 246KB
input1_A3.png 238KB
input1_A5.png 237KB
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