CN115988188A - Color balance correction method, device, electronic equipment and storage medium - Google Patents

Abstract

The present application provides a color balance correction method, device, electronic equipment and storage medium. Wherein, the method includes: determining the first color pixel and the second color pixel corresponding to the pixel to be corrected, the first color pixel is a pixel in the same channel as the pixel to be corrected, and the second color pixel is a pixel in a different channel from the pixel to be corrected Pixels of the same color; calculate multiple gradient values of the pixel to be corrected at the current position according to the first color pixel; calculate multiple eigenvalues of multiple second color pixels according to the second color pixel; calculate according to multiple gradient values and multiple eigenvalues The color balance correction value of the pixel to be corrected, so as to perform color balance correction on the pixel to be corrected by the color balance correction value. In this embodiment of the present application, various predictions are made on the correction value of the pixel to be corrected based on multiple gradient values and multiple eigenvalues, and the color balance correction value obtained based on the multiple gradient values and multiple eigenvalues can improve the color balance. Accuracy of balance correction values.

Description

Color balance correction method, device, electronic device and storage medium

technical field

The present application relates to the field of image processing, in particular, to a color balance correction method, device, electronic equipment and storage medium.

Background technique

Due to the crosstalk phenomenon inside the sensor, that is, the light of adjacent pixels leaks to the current pixel in some way, which affects the pixel value of the current pixel. Affected by the manufacturing process of the sensor, the above-mentioned light leakage degree is different in the horizontal and vertical directions, which will cause the same color pixels to have different performances for the same light source, so in the final imaging, a grid will appear on the image shape defects, causing serious picture quality problems.

At present, the common way to overcome the above-mentioned problems is to analyze and correct the crosstalk, so as to alleviate the problem of color imbalance. Or use image analysis to artificially judge whether there is color imbalance, so as to make corresponding corrections. However, the causes of crosstalk are very complex, involving various factors such as lenses, sensors, and light sources. Therefore, it is relatively inaccurate to correct the color imbalance by analyzing the degree of crosstalk. However, image analysis is used to correct color imbalance, because it is impossible to judge whether the different performance of pixels of the same color on the image comes from color imbalance or is really a problem with the texture itself. If there is a misjudgment, it may cause problems such as poor resolution of the image.

Contents of the invention

In view of this, the purpose of the embodiments of the present application is to provide a color balance correction method, device, electronic device and readable storage medium, which can improve the accuracy of the color balance correction value, and further improve the accuracy of color imbalance correction.

In the first aspect, the embodiment of the present application provides a color balance correction method, including: determining the first color pixel and the second color pixel corresponding to the pixel to be corrected, the first color pixel is the same as the pixel to be corrected channel, the second color pixel is the same color pixel that is not in the same channel as the pixel to be corrected; calculate multiple gradient values of the pixel to be corrected at the current position according to the first color pixel; according to the first color pixel Calculating a plurality of eigenvalues of a plurality of pixels of the second color for two color pixels; calculating a color balance correction value of the pixel to be corrected according to a plurality of gradient values and a plurality of eigenvalues, so as to pass the color balance The correction value performs color balance correction on the pixel to be corrected.

In the above implementation process, multiple gradient values are calculated according to the pixels of the first color, and multiple eigenvalues are calculated for the pixels of the second color, so as to make multiple predictions of the correction value of the pixel to be corrected through the multiple gradient values and the multiple eigenvalues, And the color balance correction value obtained based on the multiple gradient values and the multiple feature values can improve the accuracy of the color balance correction value, thereby improving the accuracy of the color balance correction.

In one embodiment, the color balance correction value of the pixel to be corrected is calculated according to the plurality of gradient values and the plurality of feature values, so as to color the pixel to be corrected by using the color balance correction value Balance correction, comprising: arranging and combining the plurality of gradient values and the plurality of feature values and adding them together to obtain an estimated value of the pixel of the second color; according to the estimated value of the pixel of the second color and calculating a color balance correction value of the pixel to be corrected with the pixel value of the pixel to be corrected, so as to perform color balance correction on the pixel to be corrected by using the color balance correction value.

In the above implementation process, multiple estimated values of pixels of the second color are obtained by arranging and combining multiple gradient values and multiple eigenvalues, and various predictions can be made on the correction value of the pixel to be corrected, which improves the accuracy of the pixel to be corrected. Pixel-corrected value prediction accuracy.

In one embodiment, the color balance correction value of the pixel to be corrected is calculated according to the estimated value of the pixel of the second color and the pixel value of the pixel to be corrected, so that the color balance correction value can be used to correct the Performing color balance correction on the pixel to be corrected includes: performing filtering processing on the estimated value of the second color pixel and the pixel value of the pixel to be corrected to obtain the final estimated value of the second color pixel; Perform weighted average processing on the final estimated value of the two-color pixel and the pixel value of the pixel to be corrected to obtain a color balance correction value of the pixel to be corrected, so as to perform color balance on the pixel to be corrected by using the color balance correction value Correction.

In the above implementation process, after the estimated value of the pixel of the second color is determined, the estimated value of the pixel of the second color is filtered to eliminate interference, thereby improving the accuracy of the final estimated value of the pixel of the second color. Then, by weighting the final estimated value of the second color pixel and the pixel value of the pixel to be corrected, the difference between the pixel to be corrected and the second color pixel is balanced, and the accuracy of color balance correction for the pixel to be corrected is improved. .

In one embodiment, if the pixel to be corrected is an edge pixel of the target window, before determining the first color pixel and the second color pixel corresponding to the pixel to be corrected, the method further includes: using the pixel to be corrected The axis where the adjacent edge pixels are located is the central axis, and the pixels on the blank side of the pixel to be corrected are mirror-compensated by the pixel on the pixel side of the pixel to be corrected.

In the above implementation process, for the pixels to be corrected on the edge of the target window, before the calculation of the color balance correction value, the pixels on the blank side are mirrored to complement the pixels on the side with pixels, so that when the pixels to be corrected are calculated , multiple predictions can be made on the correction values of the pixels to be corrected according to the multiple pixels in the target window, which can improve the accuracy of the color balance correction value.

In one embodiment, the pixel to be corrected is a green pixel.

In the above implementation process, since there are two channels in each pixel of the green pixel, the pixel values of the two green pixel channels are different due to the difference in the horizontal and vertical proximity, which causes the green pixels of the two channels to be unbalanced. By performing the color balance correction value on the green pixel, the green balance correction is performed on the green pixel through the color balance correction value, so that the pixel difference between the green pixels of the two channels is balanced, and the image quality is improved.

In one embodiment, the calculating multiple gradient values of the pixel to be corrected at the current position according to the first color pixel includes: calculating the pixel to be corrected according to a part of the first color pixel in the first color pixel Multiple gradient values at the current position.

In the above implementation process, by calculating multiple gradient values of the pixel to be corrected at the current position according to part of the first color pixels in the first color pixels, multiple possibilities for the gradient value calculation are increased to obtain more gradient values , multiple predictions of the correction value of the pixel to be corrected can be made through multiple gradient values, which improves the accuracy of prediction of the correction value of the pixel to be corrected.

In one embodiment, the calculating the feature values of the plurality of second color pixels according to the second color pixels includes: calculating a plurality of the second color pixels according to part of the second color pixels in the second color pixels The feature value of the second color pixel.

In the above implementation process, by calculating the eigenvalues of multiple second color pixels according to part of the second color pixels in the second color pixels, multiple possibilities for the calculation of the eigenvalues are increased to obtain more eigenvalues, by Multiple feature values can make multiple predictions of the correction value of the pixel to be corrected, which improves the accuracy of prediction of the correction value of the pixel to be corrected.

In the second aspect, the embodiment of the present application also provides a color balance correction device, including: a determination module, configured to determine a first color pixel and a second color pixel corresponding to the pixel to be corrected, the first color pixel is the same as the The pixel to be corrected is in the same channel, and the pixel of the second color is a pixel of the same color that is not in the same channel as the pixel to be corrected; the first calculation module is used to calculate the pixel to be corrected according to the pixel of the first color A plurality of gradient values at the current position; a second calculation module, configured to calculate a plurality of feature values of the second color pixel according to the second color pixel; a third calculation module, configured to calculate a plurality of eigenvalues of the second color pixel according to the plurality of gradient values and A color balance correction value of the pixel to be corrected is calculated for the plurality of eigenvalues, so as to perform color balance correction on the pixel to be corrected by using the color balance correction value.

In the third aspect, the embodiment of the present application also provides an electronic device, including: a processor, a memory, the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the machine-readable When the instructions are executed by the processor, the above first aspect, or the steps of the method in any possible implementation manner of the first aspect are executed.

In the fourth aspect, the embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned first aspect, or any of the first aspects, can be executed. Steps of a color balance correction method in a possible implementation.

In order to make the above objects, features and advantages of the present application more comprehensible, the following specific embodiments are described in detail in conjunction with the accompanying drawings.

Description of drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the accompanying drawings used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, so It should be regarded as a limitation on the scope, and those skilled in the art can also obtain other related drawings based on these drawings without creative work.

FIG. 1 is a schematic diagram of the distribution of color pixels in every 2x2 pixels provided by the embodiment of the present application;

FIG. 2 is a flow chart of a color balance correction method provided in an embodiment of the present application;

3 is a schematic diagram of the distribution of color pixels in 5x5 pixels provided by the embodiment of the present application;

FIG. 4 is a schematic diagram of the distribution of color pixels in 4x6 pixels provided by the embodiment of the present application;

FIG. 5 is a schematic diagram of the distribution of color pixels in 4x6 pixels provided by the embodiment of the present application. The pixel to be corrected is Gb01, and the image after mirroring is completed;

6 is a schematic diagram of the distribution of color pixels in 4x6 pixels provided by the embodiment of the present application. The pixel to be corrected is Gr06, and the image after mirroring is completed;

7 is a schematic diagram of the distribution of color pixels in 10x10 pixels provided by the embodiment of the present application;

FIG. 8 is a schematic diagram of functional modules of a color balance correction device provided by an embodiment of the present application;

FIG. 9 is a schematic block diagram of an electronic device provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

It should be noted that like numerals and letters denote similar items in the following figures, therefore, once an item is defined in one figure, it does not require further definition and explanation in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second" and the like are only used to distinguish descriptions, and cannot be understood as indicating or implying relative importance.

For the convenience of understanding, the applicable scenarios of the embodiments of the present application are first described in detail.

In order to increase the light sensitivity of a single pixel, the image sensor of the camera usually adopts a Bayer Pattern (Chinese name: Bayer array) structure. That is, through an optical mask, each pixel of the image can only receive light of a certain wavelength among red, green, and blue. Therefore, each pixel of the output image of the image sensor can also be divided into three types: red, green, and blue. And because the human eye is more sensitive to green light in natural light, the ratio of green light pixels in the Bayer Pattern is twice that of red and blue. As a result, every 2x2 pixels in the output of the image sensor appear in a form similar to that shown in Figure 1. In Figure 1, R is a red pixel, B is a blue pixel, and Gr is a green pixel, and its horizontal neighbors is a red pixel, its vertical neighbor is a blue pixel, Gb is a green pixel, its horizontal neighbor is a blue pixel, and its vertical neighbor is a red pixel.

It can be found from Figure 1 that Gr and Gb are both green pixels, but their horizontal and vertical neighbors are different. Obviously, Gr is crosstalked by R in the horizontal direction, and crosstalked by B in the vertical direction. Gb is crosstalked by B in the horizontal direction, and crosstalked by R in the vertical direction. Based on this difference, Gr and Gb, which are both green pixels, have different performances for the same light source, that is, different pixel values.

If such Gr and Gb are all over the image, when the performance of these two pixels is different, in the final imaging, grid-like defects will appear on the image, causing serious image quality problems. This problem is known as color imbalance.

In view of this, the inventor of the present application proposes a color balance correction method, by calculating multiple gradient values of the pixel to be corrected at the current position according to the pixels in the same channel as the pixel to be corrected, and the same color as the pixel to be corrected is not in the same channel The pixel calculates multiple eigenvalues of multiple second color pixels, and makes multiple predictions of the correction value of the pixel to be corrected through the multiple eigenvalues and gradient values, and then integrates these multiple predictions to obtain a more accurate The color balance correction value, and the color imbalance can be corrected by using the color balance correction value, thereby improving the image quality.

Please refer to FIG. 2 , which is a flow chart of the color balance correction method provided by the embodiment of the present application. The specific process shown in FIG. 2 will be described in detail below.

Step 201, determine the first color pixel and the second color pixel corresponding to the pixel to be corrected.

Wherein, the pixel of the first color is a pixel in the same channel as the pixel to be corrected, and the pixel of the second color is a pixel of the same color not in the same channel as the pixel to be corrected.

In the currently commonly used Bayer Pattern structure, the proportion of green pixels is twice that of red and blue. Therefore, in the output of the image sensor, there are two green pixel channels for every 2x2 pixels. Because the horizontal and vertical proximity of the two green pixel channels are different, the pixel values are different, which causes the green pixels of the two channels to be unbalanced, and any green pixel in the two channels can be a pixel to be corrected.

The same channel here refers to a channel that receives the same crosstalk in the horizontal and vertical directions. The relationship between the pixel to be corrected, the first pixel and the second pixel will be further described below by taking the BayerPattern structure as an example in conjunction with the diagram. As shown in FIG. 3, in FIG. 3, Gr00, Gr02, Gr04, Gr20, Gr22, Gr24, Gr40, Gr42, and Gr44 are pixels of the same channel, and Gb11, Gb13, Gb31, and Gb33 are pixels of the same channel.

Exemplarily, if the pixel to be corrected is Gr22, the first color pixels are Gr00, Gr02, Gr04, Gr20, Gr24, Gr40, Gr42, and the second color pixels are Gb11, Gb13, Gb31, Gb33. If the pixel to be corrected is Gb11, the first color pixels are Gb13, Gb31, Gb33, and the second color pixels are Gr00, Gr02, Gr04, Gr20, Gr24, Gr40, Gr42.

The above-mentioned first color pixels and second color pixels are color pixels in the image window.

Understandably, in addition to the commonly used Bayer Pattern structure mentioned above, it is like a sensor structure. The proportion of yellow pixels in the Sensor structure is twice that of red and blue. Therefore, in the output of the image sensor, there are two channels of yellow pixels for every 2×2 pixels. Then the pixel to be corrected in this structure is a yellow pixel.

It is only exemplary that the pixel to be corrected is a yellow pixel or a green pixel, and the determination of the pixel to be corrected can be determined according to the structure of the image sensor, which is not specifically limited in this application.

Step 202, calculating a plurality of gradient values of the pixel to be corrected at the current position according to the first color pixel.

The multiple gradient values here can be calculated by operators such as Sobel operator and Laplacian operator.

Exemplarily, as shown in FIG. 3, if the pixel to be corrected in FIG. 3 is Gr22, the calculation of multiple gradient values by the first color pixel can be performed using the following method:

Gr_Grad_1=Gr22-(Gr02+Gr20+Gr24+Gr42)/4.0;

Gr_Grad_2=Gr22-(Gr00+Gr04+Gr040+Gr44)/4.0;

Wherein, Gr_Grad_1 is the first gradient value, Gr_Grad_2 is the second gradient value, and Gr00, Gr02, Gr04, Gr20, Gr22, Gr24, Gr40, Gr42, and Gr44 are the pixel values of each pixel.

Of course, in addition to the above algorithm, the calculation of multiple gradient values through the first color pixel can also be calculated using the following method:

Gr_Grad_3=Gr22-(Gr20+Gr24)/2.0;

Gr_Grad_4=Gr22-(Gr02+Gr42)/2.0;

Wherein, Gr_Grad_3 is the third gradient value, Gr_Grad_4 is the fourth gradient value, and Gr02, Gr20, Gr22, Gr24, and Gr42 are the pixel values of each pixel.

It can be understood that the above-mentioned algorithm for calculating multiple gradient values through the first color pixels is only exemplary, and the calculation method for calculating multiple gradient values through the first color pixels can be adjusted according to actual conditions, and this application does not make specific limitations.

Step 203 , calculating multiple feature values of multiple second color pixels according to the second color pixels.

The multiple eigenvalues here can be calculated by methods such as average value, weighted average value, and average value of the direction to be treated.

Exemplarily, as shown in FIG. 3, if the pixel to be corrected in FIG. 3 is Gr22, then the calculation of multiple eigenvalues by the second color pixel can be calculated using the following method:

Gb_Val_1=(Gb11+Gb13+Gb31+Gb33)/4.0;

Gb_Val_2=(Gb11+Gb33)/2.0;

Gb_Val_3=(Gb31+Gb13)/2.0;

Wherein, Gb_Val_1 is the first eigenvalue, Gb_Val_2 is the second eigenvalue, Gb_Val_3 is the third eigenvalue, and Gb11, Gb13, Gb31, Gb33 are the pixel values of each pixel.

Of course, in addition to the above method, the calculation of multiple eigenvalues through the second color pixel can also be calculated using the following method:

Gb_Val_4=Medium_Filter(Gb11,Gb13+Gb31+Gb33);

Gb_Val_5=Max((Gb11+Gb33)/2.0, (Gb31+Gb13)/2.0);

Wherein, Gr_Grad_4 is the fourth feature value, Gr_Grad_5 is the fifth feature value, and Gb11, Gb13, Gb31, and Gb33 are the pixel values of each pixel.

It can be understood that the above-mentioned algorithm for calculating multiple eigenvalues by using pixels of the second color is only exemplary, and the calculation method for calculating multiple eigenvalues by using pixels of the second color can be adjusted according to actual conditions, and this application does not make specific limitations.

Step 204, calculate the color balance correction value of the pixel to be corrected according to the multiple gradient values and the multiple feature values, so as to perform color balance correction on the pixel to be corrected by the color balance correction value.

Here, the color balance correction value is the corrected pixel value of the pixel to be corrected. Exemplarily, if the color balance correction value is A, the pixel value of the pixel to be corrected can be replaced by the color balance correction value, that is, the corrected pixel value of the pixel to be corrected is also A.

In the above implementation process, multiple gradient values are calculated according to the pixels of the first color, and multiple eigenvalues are calculated for the pixels of the second color, so as to make multiple predictions of the correction value of the pixel to be corrected through the multiple gradient values and the multiple eigenvalues, And the color balance correction value obtained based on the multiple gradient values and the multiple feature values can improve the accuracy of the color balance correction value, thereby improving the accuracy of the color balance correction.

In a possible implementation manner, step 204 includes: arranging and combining a plurality of gradient values and a plurality of eigenvalues and adding them together to obtain an estimated value of the second color pixel; according to the estimated value of the second color pixel and The pixel value of the pixel to be corrected calculates the color balance correction value of the pixel to be corrected, so as to perform color balance correction on the pixel to be corrected by the color balance correction value.

Understandably, if there are M gradient values and N feature values, then M×N estimated values of the second color pixels can be obtained.

Exemplarily, if the gradient value includes: a first gradient value Gr_Grad_1 and a second gradient value Gr_Grad_2. The characteristic values include: a first characteristic value Gb_Val_1, a second characteristic value Gb_Val_2 and a third characteristic value Gb_Val_3. Then the 2 gradient values and 3 eigenvalues are arranged and combined and then added together to obtain the estimated value of the second color pixel in the following 6:

Gb_Est_1=Gr_Grad_1+Gb_Val_1;

Gb_Est_2=Gr_Grad_1+Gb_Val_2;

Gb_Est_3=Gr_Grad_1+Gb_Val_3;

Gb_Est_4=Gr_Grad_2+Gb_Val_1;

Gb_Est_5=Gr_Grad_2+Gb_Val_2;

Gb_Est_6=Gr_Grad_2+Gb_Val_3;

Wherein, Gb_Est_1, Gb_Est_2, Gb_Est_3, Gb_Est_4, Gb_Est_5, and Gb_Est_6 are estimated values of pixels of the second color.

In the above implementation process, multiple estimated values of pixels of the second color are obtained by arranging and combining multiple gradient values and multiple eigenvalues, and various predictions can be made on the correction value of the pixel to be corrected, which improves the accuracy of the pixel to be corrected. Pixel-corrected value prediction accuracy.

In a possible implementation manner, calculating the color balance correction value of the pixel to be corrected according to the estimated value of the second color pixel and the pixel value of the pixel to be corrected, so as to perform color balance correction on the pixel to be corrected by using the color balance correction value, including: Perform filtering processing on the estimated value of the second color pixel and the pixel value of the pixel to be corrected to obtain the final estimated value of the second color pixel; perform weighted average processing on the final estimated value of the second color pixel and the pixel value of the pixel to be corrected , to obtain the color balance correction value of the pixel to be corrected, so as to perform color balance correction on the pixel to be corrected by the color balance correction value.

The filtering process here may be low-pass filtering, median filtering, maximum filtering, minimum filtering, and the like. The filtering processing manner may be selected according to actual conditions, and is not specifically limited in this application.

Exemplarily, if median filtering is performed on the estimated value of the second color pixel and the pixel to be corrected in the above example, the following result can be obtained:

Gb_Est = Median_Filter(Gr22, Gb_Est_1, Gb_Est_2, Gb_Est_3, Gb_Est_4, Gb_Est_5, Gb_Est_6);

Wherein, Gb_Est is the final estimated value of the second color pixel, Gb_Est_1, Gb_Est_2, Gb_Est_3, Gb_Est_4, Gb_Est_5, Gb_Est_6 are the estimated values of the second color pixel, Gr22 is the pixel value of the pixel to be corrected.

After the estimated value of the second color pixel and the pixel to be corrected are subjected to median filtering, the final estimated value of the second color pixel and the pixel value of the pixel to be corrected are weighted and averaged to obtain the color balance correction value of the pixel to be corrected, Examples are as follows:

Gr22_GIC=(Gb_Est+Gr22)/2.0;

Wherein, Gr22_GIC is the color balance correction value of the pixel to be corrected, Gb_Est is the final estimated value of the second color pixel, and Gr22 is the pixel value of the pixel to be corrected.

In the above implementation process, after the estimated value of the pixel of the second color is determined, the estimated value of the pixel of the second color is filtered to eliminate interference, thereby improving the accuracy of the final estimated value of the pixel of the second color. Then, by weighting the final estimated value of the second color pixel and the pixel value of the pixel to be corrected, the difference between the pixel to be corrected and the second color pixel is balanced, and the accuracy of color balance correction for the pixel to be corrected is improved. .

In a possible implementation, if the pixel to be corrected is an edge pixel of the target window, before step 201, the method further includes: taking the axis where the edge pixel adjacent to the pixel to be corrected is located as the central axis, and passing through the pixel to be corrected The pixels on the side are mirrored to complement the pixels on the blank side of the pixel to be corrected.

The target window here is the image window where the image is displayed.

It can be understood that if the pixel to be corrected is an edge pixel of the target window, at least one side of the pixel to be corrected has no color pixel in the horizontal or vertical direction. In order to ensure that the calculated color balance correction value of the pixel to be corrected is more accurate, the side without the color pixel can be mirror-compensated according to the existing color pixel.

Exemplarily, as shown in FIG. 4 , if the pixel to be corrected is Gb01 in FIG. 4 , there is no color pixel on the left side and the upper side of the Gb01 . The edge pixel adjacent to the pixel to be corrected is the pixel to be corrected, and in the horizontal direction, the column of the pixel where the Gb01 is located can be taken as the central axis, and the right color pixel is mirrored to the left. In the horizontal direction, the pixel of the Gb01 can be used as the central axis, and the lower side color pixels can be mirrored to the upper side to form an image as shown in FIG.

If the pixel to be corrected is Gr06 in FIG. 4, there is no color pixel on the left side of Gr06. The edge pixel adjacent to the pixel to be corrected is the black pixel on the left side of Gr06, and in the horizontal direction, the column of the black pixel on the left side of Gr06 can be used as the central axis, and the color pixel on the right side can be mirrored to the left side. After forming the image as shown in FIG. 6 , follow steps 201-204 to correct the color balance value of the Gr06.

It can be understood that the above is just an example, and the method of mirror complementing the pixels on the blank side of the pixel to be corrected by the pixel on the side of the pixel to be corrected can be adjusted according to the position of the pixel to be corrected and the distribution of the actual color pixels , this application does not make specific limitations.

In the above implementation process, for the pixels to be corrected on the edge of the target window, before the calculation of the color balance correction value, the pixels on the blank side are mirrored to complement the pixels on the side with pixels, so that when the pixels to be corrected are calculated , multiple predictions can be made on the correction values of the pixels to be corrected according to the multiple pixels in the target window, which can improve the accuracy of the color balance correction value.

In a possible implementation manner, the pixel to be corrected is a green pixel.

In the above implementation process, since there are two channels in each pixel of the green pixel, the pixel values of the two green pixel channels are different due to the difference in the horizontal and vertical proximity, which causes the green pixels of the two channels to be unbalanced. By performing the color balance correction value on the green pixel, the green balance correction is performed on the green pixel through the color balance correction value, so that the pixel difference between the green pixels of the two channels is balanced, and the image quality is improved.

In a possible implementation manner, step 202 includes: calculating a plurality of gradient values of the pixel to be corrected at the current position according to part of the first color pixels in the first color pixels.

It can be understood that when calculating the gradient value of the plurality of first color pixels corresponding to the pixel to be corrected, the gradient value can be calculated through all the first color pixels of the target window, or only through the target Part of the pixels of the first color in the window calculate the gradient value.

Exemplarily, as shown in FIG. 3 , if the pixel to be corrected is Gr22, the gradient value of Gr22 at the current position can be calculated through Gr00, Gr02, Gr04, Gr20, Gr24, Gr40, Gr42, and Gr44. The gradient value of Gr22 at the current position can also be calculated through Gr00, Gr02, Gr04, Gr40, Gr42, and Gr44, and the lateral gradient value of Gr22 at the current position can be calculated through Gr00, Gr02, Gr04, Gr40, Gr42, and Gr44. The gradient value of Gr22 at the current position can also be calculated through Gr00, Gr20, Gr40, Gr04, Gr24, and Gr44, and the longitudinal gradient value of Gr22 at the current position can be calculated through Gr00, Gr20, Gr40, Gr04, Gr24, and Gr44. Of course, the gradient value of Gr22 at the current position can also be calculated through Gr04, Gr40, Gr00, and Gr44, and the gradient value of the 45° angle of Gr22 at the current position can be calculated through Gr04, Gr40, Gr00, and Gr44.

The above calculation of multiple gradient values of the pixel to be corrected at the current position through the first color pixel can be calculated by the first color pixel adjacent to the pixel to be corrected, or by the first color pixel not adjacent to the pixel to be corrected One color pixel for calculation. The selection of the first color pixel can be adjusted according to the actual situation, which is not specifically limited in this application.

Exemplarily, as shown in FIG. 7, if the pixel to be corrected is Gr113, then Gr100, Gr104, Gr121, and Gr125 can be selected to calculate the gradient value, and Gr106, Gr108, Gr1117, and Gr1119 can be selected to calculate the gradient value.

In the above implementation process, by calculating multiple gradient values of the pixel to be corrected at the current position according to part of the first color pixels in the first color pixels, multiple possibilities for the gradient value calculation are increased to obtain more gradient values , multiple predictions of the correction value of the pixel to be corrected can be made through multiple gradient values, which improves the accuracy of prediction of the correction value of the pixel to be corrected.

In a possible implementation manner, step 203 includes: calculating feature values of multiple second color pixels according to part of the second color pixels in the second color pixels.

It can be understood that when calculating the eigenvalues of the plurality of pixels of the second color corresponding to the pixel to be corrected, the eigenvalues can be calculated through all the pixels of the second color in the target window, or only through the target Part of the pixels of the second color in the window calculate the feature value.

Exemplarily, as shown in FIG. 7 , if the pixel to be corrected is Gr113, the feature value of the pixel of the second color may be calculated through Gb107 , Gb108 , Gb112 , and Gb113 . The feature value of the second color pixel can also be calculated through Gb102, Gb107, Gb112, Gb117, Gb122, and the vertical feature value of the second color pixel can be calculated through Gb102, Gb107, Gb112, Gb117, Gb122. The feature value of the second color pixel can also be calculated through Gb105, Gb106, Gb107, Gb108, Gb109, and the horizontal feature value of the second color pixel can be calculated through Gb105, Gb106, Gb107, Gb108, Gb109. Of course, the eigenvalues of the second color pixels can also be calculated through Gb104, Gb108, Gb112, Gb116, and Gb120, and the 45° angle eigenvalues of the second color pixels can be calculated through Gb104, Gb108, Gb112, Gb116, and Gb120.

The aforementioned calculation of the eigenvalue of the second color pixel by the second color pixel may be performed by the second color pixel adjacent to the pixel to be corrected, or by the second color pixel not adjacent to the pixel to be corrected Calculation. The selection of the pixels of the second color can be adjusted according to the actual situation, which is not specifically limited in this application.

Exemplarily, as shown in FIG. 7, if the pixel to be corrected is Gr113, Gb107, Gb108, Gb112, and Gb113 can be selected to calculate the feature value, and Gb100, Gb104, Gb120, and Gb124 can be selected to calculate the feature value, etc.

In the above implementation process, by calculating the eigenvalues of multiple second color pixels according to part of the second color pixels in the second color pixels, multiple possibilities for the calculation of the eigenvalues are increased to obtain more eigenvalues, by Multiple feature values can make multiple predictions of the correction value of the pixel to be corrected, which improves the accuracy of prediction of the correction value of the pixel to be corrected.

Based on the same application idea, the embodiment of the present application also provides a color balance correction device corresponding to the color balance correction method. Since the problem-solving principle of the device in the embodiment of the present application is similar to the aforementioned embodiment of the color balance correction method, this application For the implementation of the device in the embodiment, reference may be made to the description in the embodiment of the above method, and repeated descriptions will not be repeated.

Please refer to FIG. 8 , which is a schematic diagram of functional modules of a color balance correction device provided by an embodiment of the present application. Each module in the color balance correction device in this embodiment is used to execute each step in the above method embodiment. The color balance correction device includes a determination module 301, a first calculation module 302, a second calculation module 303, and a third calculation module 304; wherein,

The determining module 301 is used to determine a first color pixel and a second color pixel corresponding to the pixel to be corrected, the first color pixel is a pixel in the same channel as the pixel to be corrected, and the second color pixel is a pixel in the same channel as the pixel to be corrected Pixels to be corrected are pixels of the same color that are not in the same channel.

The first calculation module 302 is configured to calculate multiple gradient values of the pixel to be corrected at the current position according to the first color pixel.

The second calculating module 303 is used for calculating a plurality of feature values of the pixels of the second color according to the pixels of the second color.

The third calculation module 304 is used to calculate the color balance correction value of the pixel to be corrected according to the plurality of gradient values and the plurality of feature values, so as to perform color balance on the pixel to be corrected by using the color balance correction value Correction.

In a possible implementation manner, the third calculation module 304 is further configured to: arrange and combine the plurality of gradient values and the plurality of eigenvalues, and then add them together, so as to obtain the second color pixel Estimated value; calculate the color balance correction value of the pixel to be corrected according to the estimated value of the second color pixel and the pixel value of the pixel to be corrected, so as to perform color correction on the pixel to be corrected by the color balance correction value Balance correction.

In a possible implementation manner, the third calculation module 304 is specifically configured to: filter the estimated value of the second color pixel and the pixel value of the pixel to be corrected, so as to obtain the second color pixel Final estimated value; performing weighted average processing on the final estimated value of the second color pixel and the pixel value of the pixel to be corrected to obtain the color balance correction value of the pixel to be corrected, so as to use the color balance correction value to Color balance correction is performed on the pixel to be corrected.

In a possible implementation manner, the color balance correction device further includes a complementing module, configured to: take the axis where the edge pixel adjacent to the pixel to be corrected is located as the central axis, and pass through the pixel on the side of the pixel to be corrected The pixels on the side of the blank side of the pixel to be corrected are mirror complemented.

In a possible implementation manner, the first calculation module 302 is specifically configured to: calculate a plurality of gradient values of the pixel to be corrected at the current position according to part of the first color pixels in the first color pixels.

In a possible implementation manner, the second calculation module 303 is specifically configured to: calculate feature values of a plurality of second color pixels according to part of the second color pixels in the second color pixels.

In order to facilitate the understanding of this embodiment, the electronic device that executes the color balance correction method disclosed in the embodiment of the present application is introduced in detail below.

As shown in FIG. 9 , it is a schematic block diagram of an electronic device. The electronic device 100 may include a memory 111 and a processor 113 . Those of ordinary skill in the art can understand that the structure shown in FIG. 9 is only schematic, and does not limit the structure of the electronic device 100 . For example, the electronic device 100 may also include more or fewer components than those shown in FIG. 9 , or have a different configuration than that shown in FIG. 9 .

The above-mentioned memory 111 and processor 113 are electrically connected to each other directly or indirectly, so as to realize data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines. The aforementioned processor 113 is used to execute the executable modules stored in the memory.

Wherein, the memory 111 can be, but not limited to, random access memory (Random Access Memory, referred to as RAM), read-only memory (Read Only Memory, referred to as ROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM) , Erasable Programmable Read-Only Memory (EPROM for short), Electric Erasable Programmable Read-Only Memory (EEPROM for short), etc. Wherein, the memory 111 is used to store a program, and the processor 113 executes the program after receiving the execution instruction, and the method performed by the electronic device 100 according to the process definition disclosed in any embodiment of the present application can be applied to processing In the device 113, or implemented by the processor 113.

The above-mentioned processor 113 may be an integrated circuit chip, which has a signal processing capability. Above-mentioned processor 113 can be general-purpose processor, comprises central processing unit (Central Processing Unit, be called for short CPU), network processor (Network Processor, be called for short NP) etc.; Can also be digital signal processor (digital signal processor, be called for short DSP) , Application Specific Integrated Circuit (ASIC for short), Field Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. Various methods, steps, and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.

The electronic device 100 in this embodiment may be used to execute each step in each method provided in the embodiment of this application.

In addition, an embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is run by a processor, the color balance correction method described in the above-mentioned method embodiments is executed. step.

The computer program product of the color balance correction method provided by the embodiment of the present application includes a computer-readable storage medium storing program codes, and the instructions included in the program code can be used to execute the color balance correction method described in the above method embodiments For details, please refer to the above-mentioned method embodiments, and details are not repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed devices and methods may also be implemented in other ways. The device embodiments described above are only illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functions and possible implementations of devices, methods and computer program products according to multiple embodiments of the present application. operate. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or part of code that includes one or more Executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by a dedicated hardware-based system that performs the specified function or action , or may be implemented by a combination of dedicated hardware and computer instructions.

In addition, each functional module in each embodiment of the present application may be integrated to form an independent part, each module may exist independently, or two or more modules may be integrated to form an independent part.

If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disc, etc., which can store program codes. . It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is a relationship between these entities or operations. There is no such actual relationship or order between them. Furthermore, the term "comprises", "comprises" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus comprising a set of elements includes not only those elements, but also includes elements not expressly listed. other elements of or also include elements inherent in such a process, method, article, or device. Without further limitations, an element defined by the statement "comprising..." does not exclude the presence of additional same elements in the process, method, article or device comprising said element.

The above descriptions are only preferred embodiments of the present application, and are not intended to limit the present application. For those skilled in the art, there may be various modifications and changes in the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this application shall be included within the protection scope of this application. It should be noted that like numerals and letters denote similar items in the following figures, therefore, once an item is defined in one figure, it does not require further definition and explanation in subsequent figures.

The above is only a specific implementation of the application, but the scope of protection of the application is not limited thereto. Anyone familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the application. Should be covered within the protection scope of this application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims (10)

1. A color balance correction method, comprising:

determining a first color pixel and a second color pixel corresponding to a pixel to be corrected, wherein the first color pixel is a pixel which is in the same channel with the pixel to be corrected, and the second color pixel is a pixel which is not in the same channel with the pixel to be corrected;

calculating a plurality of gradient values of the pixel to be corrected at the current position according to the first color pixel;

calculating a plurality of characteristic values of a plurality of second color pixels according to the second color pixels;

and calculating a color balance correction value of the pixel to be corrected according to the plurality of gradient values and the plurality of characteristic values so as to carry out color balance correction on the pixel to be corrected through the color balance correction value.

2. The method according to claim 1, wherein said calculating a color balance correction value of the pixel to be corrected according to the plurality of gradient values and the plurality of feature values to perform color balance correction on the pixel to be corrected by the color balance correction value comprises:

arranging and combining the plurality of gradient values and the plurality of characteristic values, and then adding the gradient values and the characteristic values to obtain an estimated value of the second color pixel;

and calculating the color balance correction value of the pixel to be corrected according to the estimated value of the second color pixel and the pixel value of the pixel to be corrected so as to carry out color balance correction on the pixel to be corrected through the color balance correction value.

3. The method according to claim 2, wherein the calculating a color balance correction value of the pixel to be corrected according to the estimated value of the second color pixel and the pixel value of the pixel to be corrected to perform color balance correction on the pixel to be corrected by the color balance correction value comprises:

filtering the estimated value of the second color pixel and the pixel value of the pixel to be corrected to obtain a final estimated value of the second color pixel;

and carrying out weighted average processing on the final estimation value of the second color pixel and the pixel value of the pixel to be corrected to obtain a color balance correction value of the pixel to be corrected, so as to carry out color balance correction on the pixel to be corrected through the color balance correction value.

4. The method according to any one of claims 1 to 3, wherein if the pixel to be corrected is an edge pixel of the target window, before the determining the corresponding first color pixel and second color pixel of the pixel to be corrected, the method further comprises:

and taking the axis of the edge pixel adjacent to the pixel to be corrected as a central axis, and performing mirror image compensation on the pixel at the blank side of the pixel to be corrected through the pixel at the pixel side of the pixel to be corrected.

5. A method according to any one of claims 1-3, characterized in that the pixel to be corrected is a green pixel.

6. The method according to any one of claims 1 to 3, wherein the calculating a plurality of gradient values of the pixel to be corrected at the current position according to the first color pixel comprises:

and calculating a plurality of gradient values of the pixels to be corrected at the current position according to part of the first color pixels.

7. The method according to any one of claims 1 to 3, wherein the calculating a plurality of feature values of the second color pixel from the second color pixel comprises:

calculating a plurality of characteristic values of the second color pixels according to a part of the second color pixels.

8. A color balance correction apparatus, comprising:

the device comprises a determining module, a correcting module and a correcting module, wherein the determining module is used for determining a first color pixel and a second color pixel corresponding to a pixel to be corrected, the first color pixel is a pixel which is in the same channel with the pixel to be corrected, and the second color pixel is a same color pixel which is not in the same channel with the pixel to be corrected;

the first calculation module is used for calculating a plurality of gradient values of the pixel to be corrected at the current position according to the first color pixel;

the second calculation module is used for calculating a plurality of characteristic values of the second color pixels according to the second color pixels;

and the third calculation module is used for calculating the color balance correction value of the pixel to be corrected according to the plurality of gradient values and the plurality of characteristic values so as to carry out color balance correction on the pixel to be corrected through the color balance correction value.

9. An electronic device, comprising: a processor, a memory storing machine-readable instructions executable by the processor, the machine-readable instructions when executed by the processor performing the steps of the method of any of claims 1 to 7 when the electronic device is run.

10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, is adapted to carry out the steps of the method according to any one of the claims 1 to 7.

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