CN113676712B - Color correction method and related device thereof - Google Patents
Color correction method and related device thereof Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/64—Circuits for processing colour signals
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/64—Circuits for processing colour signals
- H04N9/643—Hue control means, e.g. flesh tone control
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/64—Circuits for processing colour signals
- H04N9/67—Circuits for processing colour signals for matrixing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/64—Circuits for processing colour signals
- H04N9/73—Colour balance circuits, e.g. white balance circuits or colour temperature control
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Abstract
The application discloses a color correction method and a related device, wherein the color correction method comprises the following steps: acquiring color information and a color temperature estimated value of equipment to be debugged; selecting corresponding color data from a color space data table of the reference equipment according to the color information and the color temperature estimation value; obtaining a target color matrix by utilizing color data, and obtaining a source color matrix; and calculating a color correction value according to the target color matrix and the source color matrix, and correcting the color information of the equipment to be debugged by using the color correction value. By the method, the debugging efficiency of the device for debugging the color style is effectively improved.
Description
Technical Field
The present disclosure relates to the field of image processing technologies, and in particular, to a color correction method and a related device.
Background
Video monitoring is an important component of security protection, and with the development of security protection technology, the improvement of video image quality is more and more emphasized. The color is used as the most important component of the image quality, and the look and feel presented by the style characteristics of the color is often used as the first index for evaluating the video by the user.
Fig. 1 is a graph of sensor versus RGB spectral response, and fig. 2 is a graph of human eye versus RGB spectral response. As can be seen from fig. 1 and 2, the response curves of human eyes and sensors (cameras) to RGB spectra are inconsistent, and color shift usually occurs after an image is subjected to white balance treatment, so that correction of a color matrix is required for the image.
Currently, the most common way to do video color processing is CCM matrix. CCM (color correction matrix) is a color correction scheme that appears to correct the difference in response of a sensor to light by the human eye, so that the video image is closer to the physical world seen by the human eye. The existing CCM matrix is generally calibrated in advance under three color temperatures of high, medium and low respectively, a group of target CCM matrix is used in the device in real time, the device estimates the color temperature value of the current monitoring picture through emission, and then interpolation is carried out to find out the corresponding CCM matrix to be used in the device. However, in practical use, the act of calibrating the CCM in advance is to achieve color style unification of the debugged device and the target device. In the debugging process, the color style difference between the debugged equipment and the target equipment is usually judged subjectively by human eyes, each element in the 3×3 matrix of the CCM is finely adjusted according to the debugging experience of actual debugging personnel, and then the device end is validated to compare the color style difference after adjustment, so that the time and the labor are consumed in the middle process, and the method is very low in efficiency.
Disclosure of Invention
The technical problem that this application mainly solves is to provide a color correction method and its relevant device to improve the debugging efficiency of equipment debugging color style.
In order to solve the above technical problem, the present application provides a color correction method, which includes: acquiring color information and a color temperature estimated value of equipment to be debugged; selecting corresponding color data from a color space data table of the reference equipment according to the color information and the color temperature estimation value; obtaining a target color matrix by utilizing color data, and obtaining a source color matrix; and calculating a color correction value according to the target color matrix and the source color matrix, and correcting the color information of the equipment to be debugged by using the color correction value.
Wherein before the step of selecting the corresponding color data from the color space data table of the reference device according to the color information and the color temperature estimation value, the method comprises the following steps: acquiring reference color information of reference equipment at different color temperatures; and establishing a color space data table according to the reference color information.
Wherein the step of selecting corresponding color data from the color space data table of the reference device according to the color information and the color temperature estimation value comprises the following steps: and selecting Lab data corresponding to the color temperature estimated value and the color information from the color space data table according to the color information and the color temperature estimated value.
The method comprises the steps of obtaining a target color matrix by utilizing color data and obtaining a source color matrix, and comprises the following steps: converting the acquired Lab data into RGB data; and performing sRGB standard inverse operation on the RGB data to obtain a target color matrix.
Wherein the step of converting Lab data into RGB data includes: converting Lab data into XYZ data, and correcting the XYZ data; the corrected XYZ data is converted into RGB data.
The method comprises the steps of obtaining a target color matrix by utilizing color data and obtaining a source color matrix, and further comprises the following steps: obtaining an rgb three-channel value of a block where the color information is located according to the color information; and acquiring a gamma value of equipment to be debugged, and performing gamma operation on the rgb three-channel value to obtain a mapped source color matrix.
The method comprises the steps of calculating a color correction value according to a target color matrix and a source color matrix, and correcting color information of equipment to be debugged by using the color correction value, and comprises the following steps: performing matrix operation on the target color matrix and the source target matrix to obtain an initial color correction value; normalizing the initial color correction value to obtain a color correction value; and performing matrix operation by using the color correction value and a source RGB matrix of the equipment to be debugged to obtain corrected color information.
The method comprises the steps of obtaining color information and color temperature estimated values of equipment to be debugged, and comprises the following steps: and estimating the current temperature of the equipment to be debugged through an algorithm to obtain a color temperature estimated value.
The method comprises the steps of estimating the current temperature of equipment to be debugged through an algorithm to obtain a color temperature estimated value, and comprises the following steps: the white balance gain expression of the equipment under different color temperature environments is recorded in advance; and matching an actual white balance calculation result in the actual environment with the white balance gain expression to obtain a color temperature estimated value corresponding to the actual environment.
The application also provides a terminal comprising a processor and a memory coupled to each other, the memory for storing program instructions, the processor for executing the program instructions stored by the memory to implement the color correction method of any of the above embodiments.
The present application also provides a computer-readable storage medium having a computer program stored thereon for implementing the color correction method of any of the above embodiments.
The beneficial effects of this application are: compared with the traditional low efficiency of debugging CCM matrix by means of manual subjective evaluation, the color correction method has the advantages that the characteristic that color space is quantitatively expressed is fully utilized under the assistance of an intelligent detection algorithm, lab space which is closest to human eyes and perceives colors is selected, the method that the equipment to be debugged can optimally approximate to the color style of target equipment is found by means of conversion of RGB three-channel statistical values and data conversion relation among the spaces, human intervention is not needed, the color correction method is suitable for security cameras in actual working conditions, real-time conversion is effective in use in the equipment, manual pre-calibration is eliminated, and the low efficiency method by means of subjective evaluation is eliminated.
Drawings
FIG. 1 is a schematic diagram of a color correction method according to an embodiment of the present application;
FIG. 2 is a flow chart of an embodiment of creating a color space data table according to the present application;
FIG. 3 is a flow chart of an embodiment of obtaining a target color matrix according to the present application;
FIG. 4 is a feature diagram of the sRGB standard presented on a display space;
FIG. 5 is a flow chart of an embodiment of obtaining a source color matrix according to the present application;
FIG. 6 is a flowchart illustrating the step S14 of FIG. 1;
FIG. 7 is a schematic structural diagram of an embodiment of a terminal of the present application;
fig. 8 is a schematic structural diagram of an embodiment of a storage medium of the present application.
Detailed Description
The following description of the technical solutions in the embodiments of the present application will be made clearly and completely with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
It should be noted that, the process of image color migration is a process of changing the color key of an image, and it is generally desirable to change one color attribute of the image without changing other color attributes of the image. The three channels of the RGB space have a strong correlation, while the channels of the Lab space have a minimum correlation. It will therefore be very convenient to make the color of the image out in Lab space. The purpose we use XYZ color space is to mediate RGB to LAB color space conversion.
In general, AWB corrects the white color with a corresponding other color that is substantially correct, so to speak, with a somewhat lower saturation and a somewhat less offset. While CCM matrices are intended to keep white (grey) unchanged, correcting other colors to a very precise position.
It should be noted that the color space refers to a method of quantitatively describing a subset of colors. The RGB, XYZ and Lab spaces are three different color spaces describing the color subset. RGB space refers to describing a specific color in terms of three color components, red, green, and blue. The XYZ space is a mathematically defined color space, the real name of which is CIE 1931 XYZ color space. The Lab space (collectively referred to as CIRLAB) is a color space designed based on human perception of color, where L represents brightness, a represents the green to red component, and b represents the blue to yellow component.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an embodiment of a color correction method of the present application. As shown in fig. 1, the color correction method includes:
step S11: and acquiring color information and a color temperature estimated value of the equipment to be debugged.
In this embodiment, the color information of the device to be debugged is the color information of an image shot by the device to be debugged in the current monitoring scene (including the current ambient temperature), and in other embodiments, the color information acquired by the device to be debugged may also be the color information acquired by the device to be debugged. The color temperature is a measurement unit which indicates that the light contains color components, and the estimated value of the color temperature of the equipment to be debugged is the ambient temperature of the equipment to be debugged or the color temperature of the image shot by the equipment to be debugged.
The color temperature estimated value is obtained according to the color information of the image shot by the equipment to be debugged. The method specifically comprises the following steps: color temperature estimation is performed by an algorithm. In an embodiment, the white balance gain expression of the equipment to be debugged in different color temperature environments is recorded in advance in a laboratory environment, and the color temperature estimated value in the current actual environment is correspondingly obtained by matching the actual white balance calculation result of the equipment to be debugged with the white balance gain expression in the laboratory environment recorded in advance in the actual environment. There are many algorithms for obtaining the color temperature estimation value, which are not limited herein.
Step S12: and selecting corresponding color data from a color space data table of the reference equipment according to the color information and the color temperature estimation value.
And selecting color data corresponding to the color information and the color temperature estimated value from a color space data table stored by the reference equipment according to the acquired color information and the color temperature estimated value of the equipment to be debugged.
Also included before this is: and acquiring reference color information of the reference equipment at different color temperatures, and establishing a color space data table according to the reference color information. Referring to fig. 2, fig. 2 is a flowchart illustrating an embodiment of creating a color space data table according to the present application. As shown in fig. 2, includes:
step S21: and acquiring reference color information of the reference equipment at different color temperatures.
The color information acquired by the reference equipment is a standard to be debugged for the color information of the equipment to be debugged. In this embodiment, the color information acquired by the reference device is standard color information. The color information acquired by the reference equipment is taken as a debugging standard to replace the color style difference generated by subjective debugging of human eyes.
Specifically, the method is preset in a laboratory environment, and color information on a color card is acquired by using reference equipment under different color temperature environments. The color card is a standard color card and can be customized.
Step S22: and establishing a color space data table according to the reference color information.
The color space data table records Lab space data tables, and specifically builds Lab data under different color temperatures. In addition to being designed based on human perception of color, the Lab space data has a good characteristic of device independence, so that as long as the white point of the color space is given, the color space can clearly determine how each color is created and displayed, and is irrelevant to the display medium used, therefore, the deviation of the reference color record caused by factors such as devices can be reduced by using the color information on the Lab space data record standard color card as the reference color.
Specifically, please refer to table 1 for the format of the color space data table of the reference device according to the color temperature:
table 1 reference device Lab table with color temperature variation
2400k and 4800k in the table are example temperatures, and Lab data corresponding to different colors at other temperatures are included in addition to 2400k and 4800k in the table, and Lab data corresponding to other colors are included in addition to example colors (red, yellow, blue) in the table.
The manner of acquiring the color data in step S12 includes: lab data corresponding to the color information and the color temperature estimation value are selected from the above Table 1. Specifically, all color information of the monitored scene of the device to be detected is obtained, and color lookup is performed in the above two-dimensional table 1 according to the color information, for example, red and blue information is included in the current monitored scene, and the color temperature estimated value is near 2400k, then red Lab (L00, a00, b 00) and blue Lab (L02, a02, b 02) in table 1 are extracted.
Step S13: and obtaining a target color matrix by utilizing the color data, and obtaining a source color matrix.
The method comprises the following steps: a target color matrix is obtained, and a source color matrix is obtained.
Wherein the target color matrix and the source color matrix are both RGB matrices, and thus, the obtained color data needs to be converted into RGB matrices.
Specifically, a method for obtaining a target color matrix is shown in fig. 3, and fig. 3 is a schematic flow chart of an embodiment of obtaining a target color matrix in the present application, including:
step S31: and converting the acquired Lab data into XYZ data, and correcting the XYZ data.
Specifically, the acquired Lab data is converted into XYZ data according to the Lab data acquired in step S12, wherein XYZ data is a color data expression of XYZ space.
The conversion mode of Lab space data and XYZ space data is as follows:
definition f y ＝(L * +16)/116，f x ＝f y +a * /500，f z ＝f y -b * 200, wherein L * ，a * ，b * A matrix of vectors for Lab spatial data.
If f y >Delta is thenOtherwise y= (f y -16/116)3δ 2 Y n ；
If f x >Delta is thenOtherwise x= (f x -16/116)3δ 2 X n ；
If f z >Delta is thenOtherwise z= (f z -16/116)3δ 2 Z n The method comprises the steps of carrying out a first treatment on the surface of the Wherein δ=6/29.
The modification processing is also performed on the XYZ data after the Lab data is converted into the XYZ data by the above formula.
Step S32: the corrected XYZ data is converted into RGB data.
The conversion mode of the XYZ space data and the RGB space data is as follows:
R＝(X×3229543-Y×1611819-Z×569148)>>20
G＝(-X×965985+Y×1967119+Z×47422)>>20
B＝(X×55460-Y×213955+Z×1207070)>>20
the XYZ data is converted into RGB data by the above formula.
Wherein the RGB data is a color data representation of the RGB space.
Step S33: and performing sRGB standard inverse operation on the RGB data to obtain a target color matrix.
The sRGB standard is a general color standard. Specifically, since the Lab values at different color temperatures are acquired based on the target device, the color expression is subjected to sRGB conversion which is standard in display transmission, in addition to the gamma module of the device itself. The features of the standard presented on the display space are shown in fig. 4, and fig. 4 is a feature diagram of the sRGB standard presented on the display space. Therefore, after the Lab data is converted into the RGB space, an inverse operation is further required using sRGB, and the resulting RGB data is a targetRGB matrix (target color matrix) equivalent to the sourcrgb matrix (source color matrix) in the device to be debugged.
The reverse operation of the sRGB standard is similar to the reverse operation of gamma. In this embodiment, the sRGB standard may be considered as a two-dimensional table of gamma2.2 standard, and the inverse operation is to bring the three RGB channels into the ordinate of the table to find the abscissa of the corresponding mapping relationship, thereby obtaining the targetRGB matrix.
Referring to fig. 5, fig. 5 is a flowchart illustrating an embodiment of obtaining the source color matrix according to the present application. As shown in fig. 5, includes:
step S51: and obtaining the rgb three-channel value of the block where the color information is located according to the color information.
The color information is color information under the current monitoring scene acquired through equipment to be debugged, and specifically refers to color information of a monitoring object in an image after an intelligent algorithm is started.
Specifically, after color information in a current monitoring scene is obtained through intelligent detection, an average value of rgb three-channel statistics of a corresponding color area is stored, for example, when the red color is detected in the upper left corner of an image, data operation is performed on the rgb channel information of all pixel points corresponding to the red color area in the upper left corner of the image, and the obtained average value is an average rgb channel value of the red color area. And sequentially obtaining the rgb channel value of the block where the color information is located by the method.
Step S52: and acquiring a gamma value of equipment to be debugged, and performing gamma operation on the rgb three-channel value to obtain a mapped source color matrix.
Wherein the gamma value is actually a two-dimensional lookup table, the abscissa is the input value, and the ordinate is the output value. Specifically, the rgb three-way values are respectively taken as input values and are brought into a two-dimensional gamma table, and an rgb three-way output value matrix under the corresponding relationship is obtained by inquiry, wherein the rgb three-way output value matrix is a sourceRGB matrix (source color matrix).
Step S14: and calculating a color correction value according to the target color matrix and the source color matrix, and correcting the color information of the equipment to be debugged by using the color correction value.
In this embodiment, the target color matrix and the source color matrix are each a matrix composed of a plurality of three-dimensional arrays, where the dimensions of the target color matrix and the source color matrix are always the same dimensions, and how many colors of the scene corresponding to the device correspond to how many sets of data. The matrix pattern of the data is shown in table 2 below:
TABLE 2 color matrix
| R1 | G1 | B1 |
| R2 | G2 | B2 |
| R3 | G3 | B3 |
| R4 | G4 | B4 |
| / | / | / |
The expression modes of the target color matrix and the source color matrix can be shown in the table 2.
Specifically, referring to fig. 6, fig. 6 is a flow chart of an embodiment of step S14 in fig. 1. As shown in fig. 6, includes:
step S61: and performing matrix operation on the target color matrix and the source target matrix to obtain an initial color correction value.
Specifically, a target color matrix/source color matrix is calculated by matrix operation, and an initial color correction value is obtained. In this embodiment, the initial color correction value is a 3×3 matrix.
Step S62: and carrying out normalization processing on the initial color correction value to obtain a color correction value.
Specifically, normalization calculation is performed on the above 3×3 initial matrix. Assume that the 3×3 matrix result is [ c00 c01 c02; c10 c11 c12; c20 c21 c22], the normalization processing mode comprises: c02 =1-c 00-c01; c12 =1-c 10-c11; c22 =1-c 20-c21. Normalization processing is performed to ensure normalization of the initial matrix in this embodiment. The initial color correction matrix may also be constrained in other ways in other embodiments.
Wherein the color correction value is a CCM matrix.
Step S63: and performing matrix operation by using the color correction value and a source RGB matrix of the equipment to be debugged to obtain corrected color information.
Specifically, the product of the CCM matrix and the source RGB matrix is calculated by matrix operation to obtain a corrected color matrix. Specifically, the calculation formula is as follows:
the beneficial effects of this embodiment are: the color correction value needed by the equipment to be debugged is obtained through the reference equipment, and the color style of the equipment to be debugged is debugged according to the obtained color correction value, so that the image color style of the equipment to be debugged is debugged to be consistent with the color style of the reference equipment. Compared with the traditional low efficiency of debugging CCM matrix by means of artificial work, the method has the advantages that under the condition that the intelligent detection algorithm is adopted to assist, the characteristic that color space is quantitatively expressed for colors is fully utilized, lab space closest to human eyes is selected, the method that equipment to be debugged can optimally approximate to the color style of target equipment is found by converting the three-channel statistics of RGB (red, green and blue), and the data conversion relation among the spaces is utilized.
The application further provides a terminal, please refer to fig. 7, fig. 7 is a schematic structural diagram of an embodiment of the terminal in the application.
The terminal 70 comprises a processor 71 and a memory 72 coupled to each other, the processor 71 being adapted to execute program instructions stored in the memory 72 for implementing the steps of any of the method embodiments described above or for correspondingly performing the steps of the color correction method of any of the method embodiments described above. The terminal may include, in addition to the above-mentioned processor and memory, a touch screen, a printing component, a communication circuit, etc., as required, and is not limited herein.
In particular, the processor 71 is operative to control itself and the memory 72 to implement the steps in any of the color correction method embodiments described above. The processor 71 may also be referred to as a CPU (Central Processing Unit ). The processor 71 may be an integrated circuit chip with signal processing capabilities. The processor 71 may also be a general purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a Field programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. In addition, the processor 71 may be commonly implemented by a plurality of integrated circuit chips.
Referring to fig. 8, fig. 8 is a schematic structural diagram of an embodiment of a computer readable storage medium 80.
The computer-readable storage medium 80 comprises a computer program 801 stored thereon, which computer program 801, when executed by the above-mentioned processor, implements the steps of any of the method embodiments described above or the steps of the color correction method of the method embodiments described above, which correspond to the steps performed.
In particular, the integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium 80. Based on such understanding, the technical solution of the present application, or a part contributing to the prior art or all or part of the technical solution, may be embodied in the form of a software product stored in a storage medium 80, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing description is only exemplary embodiments of the present application and is not intended to limit the scope of the present application, and all equivalent structures or equivalent processes using the descriptions and the drawings of the present application, or direct or indirect application in other related technical fields are included in the scope of the present application.
Claims (6)
1. A color correction method, comprising:
acquiring color information and a color temperature estimated value of equipment to be debugged; the color temperature estimation value is obtained according to the color information of the image shot by the equipment to be debugged;
acquiring reference color information of reference equipment at different color temperatures;
establishing the color space data table according to the reference color information;
selecting Lab data corresponding to the color temperature estimated value and the color information from the color space data table according to the color information and the color temperature estimated value;
converting the Lab data into XYZ data and correcting the XYZ data;
converting the corrected XYZ data into RGB data;
performing sRGB standard inverse operation on the RGB data to obtain a target color matrix;
obtaining an rgb three-channel value of a block where the color information is located according to the color information;
the gamma value of the equipment to be debugged is obtained, gamma operation is carried out on the rgb three-channel value, and a mapped source color matrix is obtained;
and calculating a color correction value according to the target color matrix and the source color matrix, and correcting the color information of the equipment to be debugged by using the color correction value.
2. The color correction method according to claim 1, wherein the step of calculating a color correction value from the target color matrix and the source color matrix and correcting the color information of the device to be debugged using the color correction value includes:
performing matrix operation on the target color matrix and the source color matrix to obtain an initial color correction value;
normalizing the initial color correction value to obtain the color correction value;
and performing matrix operation by using the color correction value and a source RGB matrix of the equipment to be debugged to obtain corrected color information.
3. The color correction method according to claim 1, wherein the step of acquiring color information and color temperature estimation values of the device to be debugged includes:
and estimating the current temperature of the equipment to be debugged through an algorithm to obtain the color temperature estimated value.
4. The color correction method according to claim 3, wherein the step of estimating the current temperature of the device to be debugged by an algorithm to obtain the color temperature estimation value comprises the steps of:
the white balance gain expression of the equipment under different color temperature environments is recorded in advance;
and matching an actual white balance calculation result in an actual environment with the white balance gain expression to obtain the color temperature estimated value corresponding to the actual environment.
5. An electronic terminal comprising a processor and a memory coupled to each other, the memory storing program instructions, the processor configured to execute the program instructions stored in the memory to implement the color correction method of any of claims 1-4.
6. A computer-readable storage medium, wherein the computer-readable storage medium has a computer program stored thereon for implementing the color correction method according to any one of claims 1 to 4.
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| EP22827281.1A EP4335106A4 (en) | 2021-06-25 | 2022-05-20 | Systems and methods for image correction |
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| CN114845094B (en) * | 2022-07-06 | 2022-09-30 | 深圳思谋信息科技有限公司 | Color correction method and device |
| CN115426485A (en) * | 2022-07-29 | 2022-12-02 | 浙江大华技术股份有限公司 | Color correction matrix adjustment method, image pickup apparatus, electronic apparatus, and storage medium |
| CN115691388B (en) * | 2022-10-31 | 2023-05-16 | 深圳市尊正数字视频有限公司 | Color management method for display equipment |
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