WO2016019751A1

WO2016019751A1 - Image processing device and method

Info

Publication number: WO2016019751A1
Application number: PCT/CN2015/080927
Authority: WO
Inventors: 李水平; 陈玮
Original assignee: 华为技术有限公司
Priority date: 2014-08-07
Filing date: 2015-06-05
Publication date: 2016-02-11
Also published as: CN104202583A; CN104202583B

Abstract

Disclosed are an image processing device and method, which belongs to the technical field of image processing. The device comprises: a sliding module for sliding in a Bayer-format image to be processed by using an M × N sliding window;a read module for reading a pixel value of a centre pixel point when the centre pixel point in the sliding window is a green pixel point; a calculation module for calculating a symmetric value of the pixel value of the centre pixel point according to the sliding window; a determination module for determining a balance output value of the centre pixel point according to the pixel value and the symmetric value of the centre pixel point;and a generation module for generating a processed image according to the balance output value of each green pixel point in the Bayer image to be processed. The problem existing in the background art that noises exist in an image due to crosstalk between adjacent pixel points in a Bayer-format image obtained through Bayer array filtering is solved; and the influence of the crosstalk between the adjacent pixel points in the image is reduced, and the image display effect is improved.

Description

Image processing device and method

The present application claims priority to Chinese Patent Application No. 2014-1038544, filed on Aug. 7, 2014, the entire disclosure of which is hereby incorporated by reference.

Technical field

The present invention relates to the field of image processing technologies, and in particular, to an image processing apparatus and method.

Background technique

Bayer (Bayer) array is one of the main technologies for color image capturing of photosensitive elements such as CCD (Charge-coupled Device) or CMOS (Complementary Metal Oxide Semiconductor) sensors.

The Bayer array simulates the sensitivity of the human eye to color, using the principle that the human eye's discrimination sensitivity to G (Green) pixels is greater than that of R (Red, Red) or B (Blue, blue) pixels, using 1 red 2 The arrangement of green 1 blue converts grayscale information into color information. As shown in Fig. 1, there is shown a schematic diagram of a 5 x 5 Bayer array 10 having 5 pixel points arranged in the lateral and longitudinal directions. Specifically, the Bayer array 10 includes a Gb channel 11 having alternating green pixel points G and blue pixel points B, and a Gr channel 12 having alternating green pixel points G and red pixel points R. Among them, the Gb channel 11 and the Gr channel 12 are arranged in phase. It can be seen from FIG. 1 that the sensor using the Bayer array actually has only one color component per pixel, and then needs to perform interpolation calculation using an interpolation algorithm to finally obtain a color image.

In the process of implementing the present invention, the inventors have found that the above technique has at least the following problem: in the Bayer format image obtained by Bayer array filtering, crosstalk will occur between adjacent pixel points, and the crosstalk will result in the final acquisition. There is noise in the color image. In a typical form of expression, this crosstalk will result in a weak, checkerboard format noise in the resulting color image.

Summary of the invention

In order to solve the crosstalk effect between adjacent pixel points in the Bayer format image obtained by Bayer array filtering in the above technology, there is noise in the finally obtained color image. The present invention provides an image processing apparatus and method. The technical solution is as follows:

In a first aspect, an image processing apparatus is provided, the apparatus comprising:

a sliding module for sliding in a Bayer format image to be processed by using a sliding window of M×N, where M and N respectively represent the length and width of the sliding window, and M and N are both greater than or equal to 3;

a reading module, configured to read a pixel value of the central pixel point when a central pixel point in the sliding window is a green pixel point, where the central pixel point refers to a center of the sliding window pixel;

a calculation module, configured to calculate, according to the sliding window, a symmetric value of a pixel value of the central pixel, where the symmetric value is used to reflect pixels of other green pixels except the central pixel in the sliding window value;

a determining module, configured to determine an equalized output value of the central pixel point according to a pixel value of the central pixel point and the symmetric value;

And a generating module, configured to generate a processed image according to the equalized output value of each green pixel point in the Bayer image to be processed.

In a first possible implementation manner of the first aspect, the sliding module includes: a selecting unit and a detecting unit;

The selecting unit is configured to select a pixel point as a starting central pixel point in the Bayer format image to be processed, and center the M×N sliding window and the starting center pixel point coincide;

The detecting unit is configured to detect whether the central pixel point is a green pixel point;

The reading module is further configured to read a pixel value of the central pixel point when the central pixel point is a green pixel point.

With reference to the first possible implementation of the first aspect, in a second possible implementation manner of the first aspect, the sliding module further includes: a sliding unit;

The sliding unit is configured to: if the central pixel point is not a green pixel point, slide the M×N sliding window, and select a next central pixel point;

The detecting unit is configured to perform the step of detecting whether the central pixel point is a green pixel point.

With reference to the first aspect, in a third possible implementation manner of the first aspect, the computing module includes: a first acquiring unit, a second acquiring unit, and a symmetric computing unit;

The first acquiring unit is configured to acquire the green on the green red Gr channel in the sliding window The first sample mean G1avg of the color pixel;

The second acquiring unit is configured to acquire a second sample mean value G2avg of the green pixel point on the green-blue Gb channel in the sliding window;

The symmetry calculation unit for calculating the center ₀ point of the pixel values of G pixels according to the first sample mean G1avg, the second sample and the mean value G2avg central pixel a pixel value G ₀ of the asymmetry value G ₀ ':

G ₀ '=G1avg+G2avg-G ₀ .

In conjunction with the third possible implementation of the first aspect, in a fourth possible implementation of the first aspect, the device further includes:

a difference calculation module, configured to calculate an absolute difference Gdiff of the first sample mean G1avg and the second sample mean G2avg: Gdiff=|G1avg-G2avg|;

a difference detecting module, configured to detect whether the absolute difference Gdiff is less than a predetermined threshold value THR, the predetermined threshold value THR>0;

The determining module is further configured to determine, according to the pixel value of the central pixel point and the symmetric value, an equalized output value of the central pixel point when the absolute difference Gdiff is less than the predetermined threshold value THR.

Combining the first aspect, the first possible implementation of the first aspect, the second possible implementation of the first aspect, the third possible implementation of the first aspect, or the fourth possible aspect of the first aspect In an embodiment, in a fifth possible implementation manner of the first aspect, the determining module includes: a third acquiring unit, a fourth obtaining unit, and an output calculating unit;

The third acquiring unit is configured to acquire a first weight W ₁ corresponding to the pixel value G ₀ of the central pixel point;

The fourth obtaining unit is configured to acquire a second weight W ₂ corresponding to the symmetric value G ₀ ';

The output calculation unit is configured to calculate, according to the weighted average algorithm, according to the first weight W ₁ , the second weight W ₂ , the pixel value G _{0 of} the central pixel point, and the symmetric value G ₀ ′ The balanced output value GIC of the central pixel point:

With reference to the fifth possible implementation manner of the first aspect, in a sixth possible implementation manner of the first aspect, the third obtaining unit includes: a first difference calculating subunit, a first mean calculating subunit And the first weight determining subunit;

The first difference calculation sub-unit is configured to calculate, for the i-th integrated sample in the sliding window, an absolute difference Cgrad[i] corresponding to the i-th integrated sample; wherein the ith The integrated sample includes a first pixel point and a second pixel point of mutually spaced pixels in the sliding window, and the absolute difference Cgrad[i] corresponding to the i-th integrated sample refers to the first pixel point The absolute difference between the pixel value and the pixel value of the second pixel, i is a positive integer;

The first mean calculating subunit is configured to calculate a mean CDavg of absolute differences corresponding to each of the integrated samples in the sliding window:

The first weight determining subunit is configured to determine a scaling value of the mean CDavg as the first weight W ₁ :

W ₁ = w × CDavg;

Where n is the number of integrated samples in the sliding window and n is a positive integer, w is a scaling factor, w>0.

With reference to the sixth possible implementation manner of the first aspect, in a seventh possible implementation manner of the first aspect, the fourth acquiring unit includes: a second difference calculating subunit, and a second mean calculating subunit a mean value determining subunit, a first determining subunit, and a second determining subunit;

The second difference calculation subunit is configured to calculate an absolute difference Ggrad[j] corresponding to the jth green sample for the jth green sample in the sliding window; wherein the jth The green sample includes a first green pixel point and a second green pixel point which are mutually adjacent pixel points in the sliding window and are both green pixel points, and the absolute difference Ggrad corresponding to the jth green sample is j] is the absolute difference between the pixel value of the first green pixel and the pixel value of the second green pixel, and j is a positive integer;

The second mean calculating subunit is configured to calculate a mean value GDavg of absolute differences corresponding to each of the green samples in the sliding window:

The mean value determining subunit is configured to determine whether the mean GDavg is greater than the first weight W ₁ ;

The first determining sub-unit, configured to, when the mean value is greater than the first GDavg weight is ₁ W, the first weight W is determined as _a second weight W _2;

The second determining sub-unit, configured to, when the average is less than the first GDavg weight is ₁ W, the average GDavg determined as the second weight W _2;

Where m is the number of green samples in the sliding window and m is a positive integer.

Combining the first aspect, the first possible implementation of the first aspect, the second possible implementation of the first aspect, the third possible implementation of the first aspect, or the fourth possible aspect of the first aspect In an eighth implementation manner of the first aspect, the generating module includes: a replacing unit and a generating unit;

The replacing unit is configured to replace, according to each green pixel point in the Bayer format image to be processed, a balanced output value of the green pixel point by a pixel value of the green pixel point;

The generating unit is configured to generate the processed image according to each of the green pixels after the replacement is completed.

In a second aspect, an image processing method is provided, the method comprising:

Using a sliding window of M×N to slide in the Bayer format image to be processed, M and N respectively represent the length and width of the sliding window, and M and N are both greater than or equal to 3;

Reading a pixel value of the central pixel point when a central pixel point in the sliding window is a green pixel point, where the central pixel point refers to a pixel point that coincides with a center of the sliding window;

Calculating a symmetric value of a pixel value of the central pixel point according to the sliding window, where the symmetric value is used to reflect a pixel value of other green pixel points in the sliding window except the central pixel point;

Determining an equalized output value of the central pixel point according to a pixel value of the central pixel point and the symmetric value;

The processed image is generated according to the equalized output values of the respective green pixel points in the Bayer image to be processed.

In a first possible implementation manner of the second aspect, the sliding of the M×N sliding window in the Bayer format image to be processed includes:

Selecting, in the Bayer format image to be processed, a pixel point as a starting central pixel point, and aligning a center of the M×N sliding window with the starting center pixel point;

Detecting whether the central pixel point is a green pixel point;

If the central pixel point is a green pixel point, the step of reading the pixel value of the central pixel point is performed.

With reference to the first possible implementation manner of the second aspect, in the second possible implementation manner of the second aspect, after the detecting the central pixel point is a green pixel point, the method further includes:

If the central pixel point is not a green pixel point, sliding the M×N sliding window and selecting a next central pixel point;

The step of detecting whether the central pixel point is a green pixel point is performed again.

With reference to the second aspect, in a third possible implementation manner of the second aspect, the calculating a symmetrical value of the pixel value of the central pixel according to the sliding window includes:

Obtaining a first sample mean G1avg of the green pixel point on the green-red Gr channel in the sliding window;

Obtaining a second sample mean value G2avg of the green pixel point on the green-blue Gb channel in the sliding window;

The mean of the first sample G1avg, the second sample and the mean value of the center pixel G2avg pixel value G ₀ of the calculated pixel values of the center pixel value G ₀ of symmetry G ₀ ':

G ₀ '=G1avg+G2avg-G ₀ .

With reference to the third possible implementation manner of the second aspect, in a fourth possible implementation manner of the second aspect, the determining, according to a pixel value of the central pixel point and the symmetric value, determining the central pixel point Before equalizing the output value, it also includes:

Calculating an absolute difference Gdiff of the first sample mean G1avg and the second sample mean G2avg: Gdiff=|G1avg-G2avg|;

Detecting whether the absolute difference Gdiff is less than a predetermined threshold value THR, the predetermined threshold value THR>0;

If the absolute difference Gdiff is smaller than the predetermined threshold value THR, the step of determining the equalized output value of the central pixel point according to the pixel value of the central pixel point and the symmetric value is performed.

Combining the second aspect, the first possible implementation of the second aspect, the second possible implementation of the second aspect, the third possible implementation of the second aspect, or the fourth possible aspect of the second aspect The embodiment, in a fifth possible implementation manner of the second aspect, the determining, according to the pixel value of the central pixel point and the symmetric value, the equalized output value of the central pixel point, including:

Obtaining a first weight W ₁ corresponding to the pixel value G ₀ of the central pixel point;

Obtaining a second weight W ₂ corresponding to the symmetric value G ₀ ';

Calculating the equalized output of the central pixel point by a weighted averaging algorithm and according to the first weight W ₁ , the second weight W ₂ , the pixel value G _{0 of} the central pixel point, and the symmetric value G ₀ ' Value GIC:

With reference to the fifth possible implementation manner of the second aspect, in a sixth possible implementation manner of the second aspect, the acquiring the first weight W ₁ corresponding to the pixel value G ₀ of the central pixel point includes :

Calculating an absolute difference Cgrad[i] corresponding to the i-th integrated sample for the i-th integrated sample in the sliding window; wherein the i-th integrated sample includes mutually spaced pixels in the sliding window a first pixel point and a second pixel point of the point, the absolute difference value Cgrad[i] corresponding to the ith integrated sample refers to a pixel value of the first pixel point and a pixel of the second pixel point The absolute difference of values, i is a positive integer;

Calculating a mean CDavg of absolute differences corresponding to each of the integrated samples in the sliding window:

Determining the scaled value of the mean CDavg as the first weight W ₁ :

W ₁ = w × CDavg;

With reference to the sixth possible implementation manner of the second aspect, in the seventh possible implementation manner of the second aspect, the acquiring the second weight W ₂ corresponding to the symmetric value G ₀ ′ includes:

Calculating an absolute difference Ggrad[j] corresponding to the jth green sample for the jth green sample in the sliding window; wherein the jth green sample comprises an oblique direction in the sliding window a first green pixel point and a second green pixel point of the adjacent pixel points and both of the green pixel points, and the absolute difference Ggrad[j] corresponding to the jth green sample refers to the first green pixel point An absolute difference between a pixel value and a pixel value of the second green pixel, j is a positive integer;

Calculating a mean value GDavg of absolute differences corresponding to each of the green samples in the sliding window:

Determining whether the mean GDavg is greater than the first weight W ₁ ;

If the mean GDavg is greater than the first weight W ₁ , determining the first weight W ₁ as the second weight W ₂ ;

If the mean GDavg is smaller than the first weight W ₁ , the mean GDavg is determined as the second weight W ₂ ;

Combining the second aspect, the first possible implementation manner of the second aspect, and the second a possible implementation, a third possible implementation of the second aspect, or a fourth possible implementation of the second aspect, in an eighth possible implementation of the second aspect, The equalized output value of each green pixel in the Bayer image generates a processed image, including:

For each green pixel in the Bayer format image to be processed, replacing the equalized output value of the green pixel point with the pixel value of the green pixel point;

The processed image is generated according to the respective green pixels after the replacement is completed.

The beneficial effects brought by the technical solutions provided by the embodiments of the present invention are:

When the central pixel of the sliding window is a green pixel, the pixel value of the central pixel is read, and the symmetric value of the pixel value of the central pixel is calculated according to the sliding window, and then determined according to the pixel value of the central pixel and the symmetric value. The equalized output value of the central pixel finally generates a processed image according to the equalized output value of each green pixel in the Bayer image to be processed; and solves the Bayer format image obtained by Bayer array filtering in the background art. The crosstalk effect between adjacent pixels causes a problem of noise in the finally obtained color image; the calculated equalized output value corrects the pixel value of the green pixel in the Bayer image to be processed, thereby minimizing the reduction The effect of crosstalk between adjacent pixels in the image improves the display of the image.

DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the present invention. Other drawings may also be obtained from those of ordinary skill in the art in light of the inventive work.

1 is a schematic diagram of a 5×5 Bayer array involved in the background art;

2 is a schematic structural diagram of an image processing apparatus according to an embodiment of the present invention;

3 is a schematic structural diagram of an image processing apparatus according to another embodiment of the present invention;

4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;

FIG. 5 is a flowchart of a method for processing an image according to an embodiment of the present invention; FIG.

FIG. 6 is a flowchart of a method for processing an image according to another embodiment of the present invention; FIG.

6B is a schematic diagram of a Bayer image to be processed related to an image processing method according to another embodiment of the present invention;

FIG. 6C is a schematic diagram of a sliding window according to an image processing method according to another embodiment of the present invention; FIG.

6D is a schematic diagram of several possible integrated samples involved in an image processing method according to another embodiment of the present invention;

FIG. 6E is a schematic diagram of several possible green samples involved in an image processing method according to another embodiment of the present invention.

detailed description

The embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

Please refer to FIG. 2, which is a structural block diagram of an image processing apparatus according to an embodiment of the present invention. The image processing apparatus can be implemented as a photosensitive element such as a CCD or a CMOS sensor by software, hardware, or a combination of both. Part or all of an electronic device. The image processing apparatus may include a slide module 210, a reading module 220, a calculation module 230, a determination module 240, and a generation module 250.

The sliding module 210 is configured to slide in the Bayer format image to be processed by using a sliding window of M×N, where M and N respectively represent the length and width of the sliding window, and M and N are both greater than or equal to 3.

The reading module 220 is configured to read a pixel value of the central pixel point when the central pixel point in the sliding window is a green pixel point, where the central pixel point refers to coincide with a center of the sliding window Pixels.

a calculation module 230, configured to calculate, according to the sliding window, a symmetric value of a pixel value of the central pixel point, where the symmetric value is used to reflect other green pixel points in the sliding window other than the central pixel point Pixel values.

The determining module 240 is configured to determine an equalized output value of the central pixel point according to the pixel value of the central pixel point and the symmetric value.

The generating module 250 is configured to generate a processed image according to the equalized output value of each green pixel point in the Bayer image to be processed.

In summary, the image processing apparatus provided in this embodiment reads the pixel value of the central pixel point when the central pixel point of the sliding window is a green pixel point, and calculates the symmetry of the pixel value of the central pixel point according to the sliding window. Value, then determining the equalized output value of the central pixel point according to the pixel value of the central pixel point and the symmetric value, and finally generating the processed image according to the equalized output value of each green pixel point in the Bayer image to be processed; Existing by Bayer array filtering In the Bayer format image, due to the crosstalk between adjacent pixel points, there is a problem of noise in the finally obtained color image; the calculated equalized output value corrects the pixel value of the green pixel in the Bayer image to be processed. , which minimizes the influence of crosstalk between adjacent pixels in the image and improves the display effect of the image.

Please refer to FIG. 3, which is a structural block diagram of an image processing apparatus according to another embodiment of the present invention. The image processing apparatus can be implemented as a photosensitive element such as a CCD or a CMOS sensor by software, hardware, or a combination of both. Part or all of the electronic device. The image processing apparatus may include a slide module 210, a reading module 220, a calculation module 230, a determination module 240, and a generation module 250.

Specifically, the sliding module 210 includes: a selecting unit 210a and a detecting unit 210b.

The selecting unit 210a is configured to select a pixel point as a starting central pixel point in the Bayer format image to be processed, and center the M×N sliding window and the starting center pixel Points coincide.

The detecting unit 210b is configured to detect whether the central pixel point is a green pixel point.

Optionally, the sliding module 210 further includes: a sliding unit 210c.

The sliding unit 210c is configured to slide the M×N sliding window and select a next central pixel if the central pixel is not a green pixel.

The detecting unit 210b is configured to perform the step of detecting whether the central pixel point is a green pixel point.

The reading module 220 is further configured to read a pixel value of the central pixel point when the central pixel point is a green pixel point.

The calculation module 230 includes: a first acquisition unit 230a, a second acquisition unit 230b, and a symmetric calculation unit 230c.

The first acquiring unit 230a is configured to acquire a first sample mean G1avg of the green pixel point on the green-red Gr channel in the sliding window.

The second acquiring unit 230b is configured to acquire a second sample mean G2avg of the green pixel point on the green-blue Gb channel in the sliding window.

The symmetry calculating unit 230c, ₀ is calculated for the central pixel a pixel value G according to the first sample mean G1avg, the second sample and the mean value of the center pixel G2avg point symmetric pixel value G ₀ Value G ₀ ':

G ₀ '=G1avg+G2avg-G ₀ .

The determining module 240 includes: a third obtaining unit 240a, a fourth obtaining unit 240b, and an output calculating unit 240c.

The third obtaining unit 240a is configured to acquire a first weight W ₁ corresponding to the pixel value G ₀ of the central pixel point.

Specifically, the third obtaining unit 240a includes: a first difference calculating subunit 240a1, a first mean calculating subunit 240a2, and a first weight determining subunit 240a3.

The first difference calculation sub-unit 240a1 is configured to calculate, for the i-th integrated sample in the sliding window, an absolute difference Cgrad[i] corresponding to the i-th comprehensive sample; wherein the ith The integrated sample includes a first pixel point and a second pixel point which are mutually spaced pixels in the sliding window, and the absolute difference Cgrad[i] corresponding to the i-th integrated sample refers to the first pixel The absolute difference between the pixel value of the point and the pixel value of the second pixel, i is a positive integer.

The first mean calculating sub-unit 240a2 is configured to calculate a mean CDavg of absolute differences corresponding to each of the integrated samples in the sliding window:

The first weight determining subunit 240a3 is configured to determine a scaling value of the mean CDavg as the first weight W ₁ :

W ₁ = w × CDavg.

Where n is the number of integrated samples in the sliding window and n is a positive integer, and w is a scaling system Number, w>0.

The fourth obtaining unit 240b is configured to acquire a second weight W ₂ corresponding to the symmetric value G ₀ '.

Specifically, the fourth obtaining unit 240b includes: a second difference calculating subunit 240b1, a second mean calculating subunit 240b2, an average judging subunit 240b3, a first determining subunit 240b4, and a second determining subunit 240b5. .

The second difference calculation sub-unit 240b1 is configured to calculate an absolute difference Ggrad[j] corresponding to the j-th green sample for the j-th green sample in the sliding window; wherein the j-th The green sample includes a first green pixel point and a second green pixel point which are mutually adjacent pixel points in the sliding window and are both green pixel points, and the absolute difference Ggrad corresponding to the jth green sample [j] refers to the absolute difference between the pixel value of the first green pixel and the pixel value of the second green pixel, and j is a positive integer.

The second mean calculating sub-unit 240b2 is configured to calculate a mean value GDavg of absolute differences corresponding to each of the green samples in the sliding window:

The mean value determining sub-unit 240b3 is configured to determine whether the mean value GDavg is greater than the first weight W ₁ .

The first determining sub-unit 240b4 is configured to determine the first weight W ₁ as the second weight W ₂ when the mean GDavg is greater than the first weight W ₁ .

The second determining subunit 240b5 is configured to determine the mean GDavg as the second weight W ₂ when the mean GDavg is less than the first weight W ₁ .

The output calculation unit 240c is configured to pass the weighted average algorithm, and according to the first weight W ₁ , the second weight W ₂ , the pixel value G _{0 of} the central pixel point, and the symmetric value G ₀ ' Calculating the equalized output value GIC of the central pixel:

The generating module 250 includes: a replacing unit 250a and a generating unit 250b.

The replacing unit 250a is configured to replace the equalized output value of the green pixel point with the pixel value of the green pixel point for each green pixel point in the Bayer format image to be processed.

The generating unit 250b is configured to generate the processed image according to each of the green pixel points after the replacement is completed.

Optionally, the device further includes: a difference calculation module 232 and a difference detection module 234.

The difference calculation module 232 is configured to calculate an absolute difference Gdiff of the first sample mean G1avg and the second sample mean G2avg: Gdiff=|G1avg-G2avg|.

The difference detecting module 234 is configured to detect whether the absolute difference Gdiff is less than a predetermined threshold value THR, and the predetermined threshold value THR>0.

The determining module 240 is further configured to determine, according to the pixel value of the central pixel point and the symmetric value, an equalized output value of the central pixel point when the absolute difference Gdiff is less than the predetermined threshold value THR .

In summary, the image processing apparatus provided in this embodiment reads the pixel value of the central pixel point when the central pixel point of the sliding window is a green pixel point, and calculates the symmetry of the pixel value of the central pixel point according to the sliding window. Value, then determining the equalized output value of the central pixel point according to the pixel value of the central pixel point and the symmetric value, and finally generating the processed image according to the equalized output value of each green pixel point in the Bayer image to be processed; The existing Bayer format image obtained by Bayer array filtering has the problem of noise in the finally obtained color image due to the crosstalk between adjacent pixel points; the Bayer image to be processed is corrected by the calculated equalized output value The pixel value of the green pixel in the image minimizes the crosstalk effect between adjacent pixels in the image, and improves the display effect of the image.

The image processing apparatus provided in this embodiment further adjusts the pixel value of the central pixel point and the symmetry value by adaptive weights, and finally obtains the equalized output value GIC of the central pixel point, which can be maximally eliminated by the adjacent pixel points. The effect of green channel imbalance caused by crosstalk avoids the generation of lattice noise while preserving the normal details in the image.

It should be noted that, when processing an image, the image processing apparatus provided by the above embodiment is only illustrated by the division of each functional module. In actual applications, the function allocation may be completed by different functional modules as needed. The internal structure of the device is divided into different functional modules to perform all or part of the functions described above. In addition, the image processing device provided by the above embodiment is the same as the method embodiment of the image processing method, and the specific implementation process is described in detail in the method embodiment, and details are not described herein again.

Please refer to FIG. 4 , which is a schematic structural diagram of an electronic device according to an embodiment of the present invention. The electronic device includes a processor 420 and a memory 440 connected to the processor 420 . One or more programs are stored in the memory 440, and the processor 420 can implement corresponding operations according to one or more programs stored in the memory 440. specific:

The processor 420 is configured to perform sliding in a Bayer format image to be processed by using a sliding window of M×N, where M and N respectively represent the length and width of the sliding window, and M and N are greater than or equal to 3;

The processor 420 is further configured to read a pixel value of the central pixel point when a central pixel point in the sliding window is a green pixel point, where the central pixel point refers to a center of the sliding window Coincident pixels;

The processor 420 is further configured to calculate, according to the sliding window, a symmetric value of a pixel value of the central pixel, where the symmetric value is used to reflect other greens in the sliding window except the central pixel The pixel value of the pixel;

The processor 420 is further configured to determine an equalized output value of the central pixel point according to a pixel value of the central pixel point and the symmetric value;

The processor 420 is further configured to generate a processed image according to the equalized output value of each green pixel in the Bayer image to be processed.

In summary, the electronic device provided in this embodiment reads the pixel value of the central pixel point when the central pixel point of the sliding window is a green pixel point, and calculates the symmetric value of the pixel value of the central pixel point according to the sliding window. And then determining the equalized output value of the central pixel point according to the pixel value of the central pixel point and the symmetric value, and finally generating the processed image according to the equalized output value of each green pixel point in the Bayer image to be processed; solving the problem in the background art The Bayer format image obtained by Bayer array filtering has the problem of noise in the finally obtained color image due to the crosstalk between adjacent pixel points; the calculated equalized output value is corrected in the Bayer image to be processed. The pixel value of the green pixel minimizes the crosstalk effect between adjacent pixels in the image and improves the display effect of the image.

In a first possible implementation of the embodiment shown in FIG. 4,

The processor 420 is further configured to select a pixel point as a starting central pixel point in the Bayer format image to be processed, and center the M×N sliding window and the center of the start Pixel points coincide;

The processor 420 is further configured to detect whether the central pixel point is a green pixel point;

The processor 420 is further configured to read a pixel value of the central pixel point when the central pixel point is a green pixel point.

In a second possible implementation manner of the embodiment shown in FIG. 4,

The processor 420 is further configured to: if the central pixel point is not a green pixel point, slide the M×N sliding window, and select a next central pixel point;

The processor 420 is further configured to perform the step of detecting whether the central pixel point is a green pixel point.

In a third possible implementation of the embodiment shown in FIG. 4,

The processor 420 is further configured to acquire a first sample mean G1avg of the green pixel point on the green-red Gr channel in the sliding window;

The processor 420 is further configured to acquire a second sample mean G2avg of the green pixel point on the green-blue Gb channel in the sliding window;

Calculating a pixel value G ₀ of the center point of the pixel processor 420, further according to the first sample mean G1avg, the second sample and the mean value of the center pixel G2avg pixel value G of a symmetrical ₀ Value G ₀ ':

G ₀ '=G1avg+G2avg-G ₀ .

In a fourth possible implementation of the embodiment shown in FIG. 4,

The processor 420 is further configured to calculate an absolute difference Gdiff of the first sample mean G1avg and the second sample mean G2avg: Gdiff=|G1avg-G2avg|;

The processor 420 is further configured to detect whether the absolute difference Gdiff is less than a predetermined threshold value THR, the predetermined threshold value THR>0;

The processor 420 is further configured to determine, according to the pixel value of the central pixel point and the symmetric value, an equalized output value of the central pixel point when the absolute difference Gdiff is less than the predetermined threshold value THR .

In a fifth possible implementation manner of the embodiment shown in FIG. 4,

The processor 420 is further configured to acquire a first weight W ₁ corresponding to a pixel value G ₀ of the central pixel point;

The processor 420 is further configured to acquire a second weight W ₂ corresponding to the symmetric value G ₀ ';

The processor 420 is further configured to pass a weighted averaging algorithm, and according to the first weight W ₁ , the second weight W ₂ , the pixel value G _{0 of} the central pixel point, and the symmetric value G ₀ ' Calculating the equalized output value GIC of the central pixel:

In a sixth possible implementation of the embodiment shown in FIG. 4,

The processor 420 is further configured to calculate an absolute difference Cgrad[i] corresponding to the i-th integrated sample for the i-th integrated sample in the sliding window; wherein the i-th integrated sample includes The first pixel point and the second pixel point of the sliding pixel are mutually spaced pixels, and the absolute difference Cgrad[i] corresponding to the i-th integrated sample refers to the pixel value of the first pixel An absolute difference from a pixel value of the second pixel, i being a positive integer;

The processor 420 is further configured to calculate a mean CDavg of absolute differences corresponding to each of the integrated samples in the sliding window:

The processor 420 is further configured to determine the scaling value of the mean CDavg as the first weight W ₁ :

W ₁ = w × CDavg;

In a seventh possible implementation of the embodiment shown in FIG. 4,

The processor 420 is further configured to calculate, according to the jth green sample in the sliding window, an absolute difference Ggrad[j] corresponding to the jth green sample; wherein the jth green sample includes The first green pixel point and the second green pixel point in the sliding window which are adjacent to each other in the oblique direction and are both green pixel points, and the absolute difference Ggrad[j] corresponding to the jth green sample is Refers to the absolute difference between the pixel value of the first green pixel and the pixel value of the second green pixel, where j is a positive integer;

The processor 420 is further configured to calculate a mean value GDavg of absolute differences corresponding to each of the green samples in the sliding window:

The processor 420 is further configured to determine whether the average value GDavg is greater than the first weight W ₁ ;

The processor 420 is further configured to determine the first weight W ₁ as the second weight W ₂ when the mean GDavg is greater than the first weight W ₁ ;

The processor 420 is further configured to determine the mean GDavg as the second weight W ₂ when the mean GDavg is less than the first weight W ₁ ;

In an eighth possible implementation manner of the embodiment shown in FIG. 4,

The processor 420 is further configured to: replace, for each green pixel point in the Bayer format image to be processed, a balanced output value of the green pixel point with a pixel value of the green pixel point;

The processor 420 is further configured to generate the processed image according to each of the green pixel points after the replacement is completed.

In addition, the electronic device provided by the embodiment further adjusts the pixel value and the symmetry value of the central pixel point by adaptive weights, and finally obtains the balanced output value GIC of the central pixel point, which can be maximally eliminated by the adjacent pixel points. The effect of the green channel imbalance caused by crosstalk avoids the generation of lattice noise while preserving the normal details in the image.

The above is an embodiment of the device of the present invention, which can be used to implement the method embodiment of the present invention. For details not disclosed in the embodiment of the apparatus of the present invention, please refer to the following method embodiments of the present invention.

Please refer to FIG. 5, which is a flowchart of a method for processing an image according to an embodiment of the present invention. The embodiment is applied to an electronic device having a photosensitive element such as a CCD or a CMOS sensor. Description. The image processing method can include the following steps:

Step 502: Sliding in the Bayer format image to be processed by using a sliding window of M×N, where M and N respectively represent the length and width of the sliding window, and M and N are both greater than or equal to 3.

Step 504: When the central pixel in the sliding window is a green pixel, the pixel value of the central pixel is read, and the central pixel refers to a pixel that coincides with the center of the sliding window.

Step 506: Calculate a symmetrical value of a pixel value of the central pixel point according to the sliding window, where the symmetrical value is used to reflect a pixel value of the green pixel point other than the central pixel point in the sliding window.

Step 508: Determine an equalized output value of the central pixel point according to the pixel value of the central pixel point and the symmetric value.

Step 510: Generate a processed image according to the equalized output values of the respective green pixel points in the Bayer image to be processed.

In summary, the image processing method provided in this embodiment reads the pixel value of the central pixel point when the central pixel point of the sliding window is a green pixel point, and calculates the symmetry of the pixel value of the central pixel point according to the sliding window. Value, then determine the equalized output value of the central pixel point according to the pixel value of the central pixel point and the symmetry value, and finally according to the balanced output of each green pixel point in the Bayer image to be processed The image is processed to generate a processed image; the problem of crosstalk between adjacent pixel points in the Bayer format image obtained by Bayer array filtering in the prior art is solved, and the noise in the finally obtained color image is solved; The calculated equalized output value corrects the pixel value of the green pixel in the Bayer image to be processed, which minimizes the crosstalk effect between adjacent pixels in the image and improves the display effect of the image.

Please refer to FIG. 6A, which is a flowchart of a method for processing an image according to another embodiment of the present invention. The image processing method is applied to an electronic device having photosensitive elements such as CCD and CMOS sensors. for example. The image processing method can include the following steps:

Step 601: Sliding in the Bayer format image to be processed by using an M×N sliding window.

In the Bayer format image to be processed, a Gb channel having an interactive green pixel point G and a blue pixel point B, and a Gr channel having an interactive green pixel point G and a red pixel point R, and the Gb channel and the Gr channel are arranged in phase .

The size of the sliding window is M×N, and M and N respectively represent the length and width of the sliding window, and M and N are both greater than or equal to 3. The size of the sliding window can be determined according to factors such as processing accuracy, device processing power, and image size.

As shown in FIG. 6B, in the present embodiment, it is assumed that the size of the Bayer format image 61 to be processed is a × b, and the size of the sliding window 62 is 5 × 5.

Specifically, this step may include the following sub-steps:

First, a pixel point is selected as the starting central pixel point in the Bayer format image to be processed, and the center of the M×N sliding window coincides with the starting center pixel point.

The center pixel refers to a pixel point that coincides with the center of the sliding window.

Second, it is detected whether the center pixel is a green pixel.

In the image processing method provided in this embodiment, in order to eliminate the lattice noise caused by the green channel imbalance caused by the crosstalk between adjacent pixel points, only the green pixel points in the Bayer format image to be processed are needed. The pixel value is corrected. In the sliding window, the processed pixel is the central pixel that coincides with the center of the sliding window, so it is necessary to detect whether the central pixel is a green pixel.

Third, if the central pixel is a green pixel, the following step 602 is performed.

In addition, if the central pixel point is not a green pixel point, the M×N sliding window is slid and the next central pixel point is selected; the second sub-step described above is performed again. Sliding window can be based on pre- The sliding rule is set to slide, for example, according to the row and column of the image, from left to right, top to bottom, and pixel by pixel.

Step 602: When the central pixel in the sliding window is a green pixel, the pixel value of the central pixel is read.

In the present embodiment, it is assumed that the pixel values of the respective pixel points in the 5 × 5 sliding window 62 are as shown in Fig. 6C. For example, the green pixel point G pixel value of the first row and the first column is D ₀₀ , the pixel value of the blue pixel point B of the first row and the second column is D ₀₁ , and the red pixel point R of the second row and the first column is The pixel value is D ₁₀ , and so on. Therefore, the pixel value of the reading center pixel is D ₂₂ .

Step 603, calculating a symmetrical value of the pixel value of the central pixel point according to the sliding window.

The symmetry value is used to reflect the pixel value of the green pixel other than the center pixel in the sliding window. In one possible algorithm, this step may include the following sub-steps:

First, the first sample mean G1avg of the green pixel on the Gr channel in the sliding window is obtained.

Wherein, the first sample mean G1avg is equal to the sum of the pixel values of the green pixel points on the Gr channel in the sliding window divided by the number of green pixel points on the Gr channel in the sliding window.

Referring to FIG. 6C, in the 5×5 sliding window 62 shown in this embodiment,

Second, the second sample mean G2avg of the green pixel on the Gb channel in the sliding window is obtained.

Wherein, the second sample mean G2avg is equal to the sum of the pixel values of the green pixel points on the Gb channel in the sliding window divided by the number of green pixel points on the Gb channel in the sliding window.

Referring to FIG. 6C, in the 5×5 sliding window 62 shown in this embodiment,

Third, the symmetric value G ₀ ' of the pixel value G ₀ of the central pixel point is calculated according to the first sample mean G1avg, the second sample mean G2avg, and the pixel value G _{0 of the} central pixel point:

G ₀ '=G1avg+G2avg-G ₀ .

Referring to FIG. 6C, in the 5×5 sliding window 62 shown in this embodiment,

Step 604, calculating an absolute difference Gdiff of the first sample mean G1avg and the second sample mean G2avg.

The absolute difference Gdiff=|G1avg-G2avg| of the first sample mean G1avg and the second sample mean G2avg.

Step 605: Detect whether the absolute difference Gdiff is less than a predetermined threshold value THR.

Wherein, the predetermined threshold value THR>0. Gdiff is used as a conditional judgment. The difference between the pixel value of the green pixel on the Gr channel and the pixel value of the green pixel on the Gb channel is the green channel caused by the crosstalk between adjacent pixels. The balance is caused by the original details in the image.

When Gdiff>THR, it is considered that the difference between the pixel value of the green pixel on the Gr channel and the pixel value of the green pixel on the Gb channel is caused by the original details in the image, and it is not necessary to correct the center pixel. The pixel value is swiped by the M×N sliding window, the next central pixel is selected, and the above-described step of detecting whether the central pixel is a green pixel is performed again.

When Gdiff<THR, the difference between the pixel value of the green pixel on the Gr channel and the pixel value of the green pixel on the Gb channel is considered to be the green channel imbalance caused by the crosstalk between adjacent pixels. As a result, the pixel value of the central pixel needs to be corrected to eliminate the influence of the green channel imbalance, and the following step 606 is performed.

Step 606, if the absolute difference Gdiff is less than the predetermined threshold value THR, the equalized output value of the central pixel point is determined according to the pixel value of the central pixel point and the symmetric value.

Specifically, this step may include the following sub-steps:

First, the first weight W ₁ corresponding to the pixel value G _{0 of} the central pixel is obtained.

1. Calculate the absolute difference Cgrad[i] corresponding to the i-th composite sample for the i-th composite sample in the sliding window.

The i-th composite sample includes a first pixel point and a second pixel point of mutually spaced pixel points in the sliding window, and the absolute difference Cgrad[i] corresponding to the i-th integrated sample refers to the pixel of the first pixel point. The absolute difference between the value and the pixel value of the second pixel, i is a positive integer.

For each composite sample, the two pixels included are two green pixels that are mutually spaced pixels, or two red pixels that are spaced apart from each other, or two blues that are spaced apart from each other. pixel. The two pixel points may be spaced apart from each other in the horizontal direction, or may be spaced apart from each other in the longitudinal direction, or may be spaced apart from each other in the oblique direction.

As shown in Figure 6D, it shows the case of several possible integrated samples.

2. Calculate the mean CDavg of the absolute difference corresponding to each comprehensive sample in the sliding window:

Where n is the number of integrated samples in the sliding window and n is a positive integer. 5 shown in Figure 6C In the sliding window 62 of ×5, the number of integrated samples is n=48, including 15 in the horizontal direction, 15 in the longitudinal direction, and 18 in the oblique direction.

3. Determine the scaling value of the mean CDavg as the first weight W ₁ :

W ₁ = w × CDavg.

Where w is the scaling factor and w>0.

Second, the second weight W ₂ corresponding to the symmetric value G ₀ ' is obtained.

1. Calculate the absolute difference Ggrad[j] corresponding to the jth green sample for the jth green sample in the sliding window.

The jth green sample includes a first green pixel point and a second green pixel point which are mutually adjacent pixel points in the sliding window and are green pixel points, and the absolute difference corresponding to the jth green sample Ggrad[j] refers to the absolute difference between the pixel value of the first green pixel and the pixel value of the second green pixel, and j is a positive integer.

As shown in Figure 6E, it shows the case of several possible green samples.

2. Calculate the mean GDavg of the absolute difference corresponding to each green sample in the sliding window:

Where m is the number of green samples in the sliding window and m is a positive integer. In the 5 x 5 sliding window 62 shown in Fig. 6C, the number of green samples is m = 16.

3. Determine whether the mean GDavg is greater than the first weight W ₁ .

4. If the mean GDavg is greater than the first weight W ₁ , the first weight W _{1 is} determined as the second weight W ₂ .

When GDavg>W ₁ ,

5. If the mean GDavg is less than the first weight W ₁ , the mean GDavg is determined as the second weight W ₂ .

When GDavg<W ₁ ,

Third, the equalized output value GIC of the central pixel point is calculated by the weighted averaging algorithm and according to the first weight W ₁ , the second weight W ₂ , the pixel value G _{0 of the} central pixel point, and the symmetric value G ₀ ':

In the image processing method provided by the embodiment, the pixel value and the symmetry value of the central pixel point are adjusted by the adaptive weight, and finally the balanced output value GIC of the central pixel point is obtained, which can be maximally eliminated. In addition to the effects of green channel imbalance caused by crosstalk between adjacent pixel points, the generation of lattice noise is avoided while retaining the normal details in the image.

Step 607: Generate a processed image according to the equalized output values of the respective green pixel points in the Bayer image to be processed.

Specifically, this step may include the following sub-steps:

First, for each green pixel in the Bayer format image to be processed, the equalized output value of the green pixel is replaced by the pixel value of the green pixel.

Second, the processed image is generated according to each green pixel after the replacement is completed.

In the case where it is determined that the difference between the pixel value of the green pixel on the Gr channel and the pixel value of the green pixel on the Gb channel is caused by the green channel imbalance, the calculated balanced output value is substituted for the green pixel. The pixel value of the point is used to implement the correction of the green pixel point, so that after the interpolation calculation by the interpolation algorithm, a color image with clear display and good detail preservation is finally obtained.

In summary, the image processing method provided in this embodiment reads the pixel value of the central pixel point when the central pixel point of the sliding window is a green pixel point, and calculates the symmetry of the pixel value of the central pixel point according to the sliding window. Value, then determining the equalized output value of the central pixel point according to the pixel value of the central pixel point and the symmetric value, and finally generating the processed image according to the equalized output value of each green pixel point in the Bayer image to be processed; The existing Bayer format image obtained by Bayer array filtering has the problem of noise in the finally obtained color image due to the crosstalk between adjacent pixel points; the Bayer image to be processed is corrected by the calculated equalized output value The pixel value of the green pixel in the image minimizes the crosstalk effect between adjacent pixels in the image, and improves the display effect of the image.

The image processing method provided by the embodiment further adjusts the pixel value and the symmetry value of the central pixel point by adaptive weights, and finally obtains the balanced output value GIC of the central pixel point, which can be maximally eliminated by the adjacent pixel points. The effect of green channel imbalance caused by crosstalk avoids the generation of lattice noise while preserving the normal details in the image.

It is to be understood that the singular forms "a", "the", "the" It should also be understood that "and/or" as used herein is meant to include any and all possible combinations of one or more of the associated listed items.

The serial numbers of the embodiments of the present invention are merely for the description, and do not represent the advantages and disadvantages of the embodiments.

A person skilled in the art may understand that all or part of the steps of implementing the above embodiments may be completed by hardware, or may be instructed by a program to execute related hardware, and the program may be stored in a computer readable storage medium. The storage medium mentioned may be a read only memory, a magnetic disk or an optical disk or the like.

The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalents, improvements, etc., which are within the spirit and scope of the present invention, should be included in the protection of the present invention. Within the scope.

Claims

An image processing apparatus, characterized in that the apparatus comprises:

a sliding module for sliding in a Bayer format image to be processed by using a sliding window of M×N, where M and N respectively represent the length and width of the sliding window, and M and N are both greater than or equal to 3;

a reading module, configured to read a pixel value of the central pixel point when a central pixel point in the sliding window is a green pixel point, where the central pixel point refers to a center of the sliding window pixel;

a calculation module, configured to calculate, according to the sliding window, a symmetric value of a pixel value of the central pixel, where the symmetric value is used to reflect pixels of other green pixels except the central pixel in the sliding window value;

a determining module, configured to determine an equalized output value of the central pixel point according to a pixel value of the central pixel point and the symmetric value;

And a generating module, configured to generate a processed image according to the equalized output value of each green pixel point in the Bayer image to be processed.
The apparatus according to claim 1, wherein the sliding module comprises: a selecting unit and a detecting unit;

The selecting unit is configured to select a pixel point as a starting central pixel point in the Bayer format image to be processed, and center the M×N sliding window and the starting center pixel point coincide;

The detecting unit is configured to detect whether the central pixel point is a green pixel point;

The reading module is further configured to read a pixel value of the central pixel point when the central pixel point is a green pixel point.
The device according to claim 2, wherein the sliding module further comprises: a sliding unit;

The sliding unit is configured to: if the central pixel point is not a green pixel point, slide the M×N sliding window, and select a next central pixel point;

The detecting unit is configured to perform the step of detecting whether the central pixel point is a green pixel point.
The device according to claim 1, wherein the calculation module comprises: a first acquisition unit, a second acquisition unit, and a symmetric calculation unit;

The first acquiring unit is configured to acquire a first sample mean G1avg of the green pixel point on the green-red Gr channel in the sliding window;

The second acquiring unit is configured to acquire a second sample mean value G2avg of the green pixel point on the green-blue Gb channel in the sliding window;

The symmetry calculation unit for calculating the center 0 point of the pixel values of G pixels according to the first sample mean G1avg, the second sample and the mean value G2avg central pixel a pixel value G 0 of the asymmetry value G 0 ':

G 0 '=G1avg+G2avg-G 0 .
The device according to claim 4, wherein the device further comprises:

a difference calculation module, configured to calculate an absolute difference Gdiff of the first sample mean G1avg and the second sample mean G2avg: Gdiff=|G1avg-G2avg|;

a difference detecting module, configured to detect whether the absolute difference Gdiff is less than a predetermined threshold value THR, the predetermined threshold value THR>0;

The determining module is further configured to determine, according to the pixel value of the central pixel point and the symmetric value, an equalized output value of the central pixel point when the absolute difference Gdiff is less than the predetermined threshold value THR.
The device according to any one of claims 1 to 5, wherein the determining module comprises: a third obtaining unit, a fourth obtaining unit, and an output calculating unit;

The third acquiring unit is configured to acquire a first weight W 1 corresponding to the pixel value G 0 of the central pixel point;

The fourth obtaining unit is configured to acquire a second weight W 2 corresponding to the symmetric value G 0 ';

The output calculation unit is configured to calculate, according to the weighted average algorithm, according to the first weight W 1 , the second weight W 2 , the pixel value G 0 of the central pixel point, and the symmetric value G 0 ′ The balanced output value GIC of the central pixel point:
The apparatus according to claim 6, wherein the third obtaining unit comprises: a first difference calculating subunit, a first mean calculating subunit, and a first weight determining subunit;

The first difference calculation sub-unit is configured to calculate, for the i-th integrated sample in the sliding window, an absolute difference Cgrad[i] corresponding to the i-th integrated sample; wherein the ith The integrated sample includes a first pixel point and a second pixel point of mutually spaced pixels in the sliding window, and the absolute difference Cgrad[i] corresponding to the i-th integrated sample refers to the first pixel point The absolute difference between the pixel value and the pixel value of the second pixel, i is a positive integer;

The first mean calculating subunit is configured to calculate a mean CDavg of absolute differences corresponding to each of the integrated samples in the sliding window:

The first weight determining subunit is configured to determine a scaling value of the mean CDavg as the first weight W 1 :

W 1 = w × CDavg;

Where n is the number of integrated samples in the sliding window and n is a positive integer, w is a scaling factor, w>0.
The apparatus according to claim 7, wherein the fourth obtaining unit comprises: a second difference calculating subunit, a second mean calculating subunit, an average judging subunit, a first determining subunit, and a second Determining a subunit;

The second difference calculation subunit is configured to calculate an absolute difference Ggrad[j] corresponding to the jth green sample for the jth green sample in the sliding window; wherein the jth The green sample includes a first green pixel point and a second green pixel point which are mutually adjacent pixel points in the sliding window and are both green pixel points, and the absolute difference Ggrad corresponding to the jth green sample is j] is the absolute difference between the pixel value of the first green pixel and the pixel value of the second green pixel, and j is a positive integer;

The second mean calculating subunit is configured to calculate a mean value GDavg of absolute differences corresponding to each of the green samples in the sliding window:

The mean value determining subunit is configured to determine whether the mean GDavg is greater than the first weight W 1 ;

The first determining sub-unit, configured to, when the mean value is greater than the first GDavg weight is 1 W, the said first weight W is determined as a second weight W 2;

The second determining sub-unit, configured to, when the average is less than the first GDavg weight is 1 W, the average GDavg determined as the second weight W 2;

Where m is the number of green samples in the sliding window and m is a positive integer.
The device according to any one of claims 1 to 5, wherein the generating module comprises: a replacing unit and a generating unit;

The replacing unit is configured to replace, according to each green pixel point in the Bayer format image to be processed, a balanced output value of the green pixel point by a pixel value of the green pixel point;

The generating unit is configured to generate the processed image according to each of the green pixels after the replacement is completed.
An image processing method, the method comprising:

Using a sliding window of M×N to slide in the Bayer format image to be processed, M and N respectively represent the length and width of the sliding window, and M and N are both greater than or equal to 3;

Reading a pixel value of the central pixel point when a central pixel point in the sliding window is a green pixel point, where the central pixel point refers to a pixel point that coincides with a center of the sliding window;

Calculating a symmetric value of a pixel value of the central pixel point according to the sliding window, where the symmetric value is used to reflect a pixel value of other green pixel points in the sliding window except the central pixel point;

Determining an equalized output value of the central pixel point according to a pixel value of the central pixel point and the symmetric value;

The processed image is generated according to the equalized output values of the respective green pixel points in the Bayer image to be processed.
The method according to claim 10, wherein the sliding using the M×N sliding window in the Bayer format image to be processed comprises:

Selecting, in the Bayer format image to be processed, a pixel point as a starting central pixel point, and aligning a center of the M×N sliding window with the starting center pixel point;

Detecting whether the central pixel point is a green pixel point;

If the central pixel point is a green pixel point, the step of reading the pixel value of the central pixel point is performed.
The method according to claim 11, wherein after detecting whether the central pixel point is a green pixel point, the method further comprises:

If the central pixel point is not a green pixel point, sliding the M×N sliding window and selecting a next central pixel point;

The step of detecting whether the central pixel point is a green pixel point is performed again.
The method according to claim 10, wherein the calculating a symmetrical value of a pixel value of the central pixel point according to the sliding window comprises:

Obtaining a first sample mean G1avg of the green pixel point on the green-red Gr channel in the sliding window;

Obtaining a second sample mean value G2avg of the green pixel point on the green-blue Gb channel in the sliding window;

The mean of the first sample G1avg, the second sample and the mean value of the center pixel G2avg pixel value G 0 of the calculated pixel values of the center pixel value G 0 of symmetry G 0 ':

G 0 '=G1avg+G2avg-G 0 .
The method according to claim 13, wherein the determining, before determining the equalized output value of the central pixel point according to the pixel value of the central pixel point and the symmetric value, further comprising:

Calculating an absolute difference Gdiff of the first sample mean G1avg and the second sample mean G2avg: Gdiff=|G1avg-G2avg|;

Detecting whether the absolute difference Gdiff is less than a predetermined threshold value THR, the predetermined threshold value THR>0;

If the absolute difference Gdiff is smaller than the predetermined threshold value THR, the step of determining the equalized output value of the central pixel point according to the pixel value of the central pixel point and the symmetric value is performed.
The method according to any one of claims 10 to 14, wherein the determining the equalized output value of the central pixel point according to the pixel value of the central pixel point and the symmetric value comprises:

Obtaining a first weight W 1 corresponding to the pixel value G 0 of the central pixel point;

Obtaining a second weight W 2 corresponding to the symmetric value G 0 ';

Calculating the equalized output of the central pixel point by a weighted averaging algorithm and according to the first weight W 1 , the second weight W 2 , the pixel value G 0 of the central pixel point, and the symmetric value G 0 ' Value GIC:
The method according to claim 15, wherein the acquiring the first weight W 1 corresponding to the pixel value G 0 of the central pixel point comprises:

Calculating an absolute difference Cgrad[i] corresponding to the i-th integrated sample for the i-th integrated sample in the sliding window; wherein the i-th integrated sample includes mutually spaced pixels in the sliding window a first pixel point and a second pixel point of the point, the absolute difference value Cgrad[i] corresponding to the ith integrated sample refers to a pixel value of the first pixel point and a pixel of the second pixel point The absolute difference of values, i is a positive integer;

Calculating a mean CDavg of absolute differences corresponding to each of the integrated samples in the sliding window:

Determining the scaled value of the mean CDavg as the first weight W 1 :

W 1 = w × CDavg;

Where n is the number of integrated samples in the sliding window and n is a positive integer, w is a scaling factor, w>0.
The method according to claim 16, wherein the acquiring the second weight W 2 corresponding to the symmetric value G 0 ' comprises:

Calculating an absolute difference Ggrad[j] corresponding to the jth green sample for the jth green sample in the sliding window; wherein the jth green sample comprises an oblique direction in the sliding window a first green pixel point and a second green pixel point of the adjacent pixel points and both of the green pixel points, and the absolute difference Ggrad[j] corresponding to the jth green sample refers to the first green pixel point An absolute difference between a pixel value and a pixel value of the second green pixel, j is a positive integer;

Calculating a mean value GDavg of absolute differences corresponding to each of the green samples in the sliding window:

Determining whether the mean GDavg is greater than the first weight W 1 ;

If the mean GDavg is greater than the first weight W 1 , determining the first weight W 1 as the second weight W 2 ;

If the mean GDavg is smaller than the first weight W 1 , the mean GDavg is determined as the second weight W 2 ;

Where m is the number of green samples in the sliding window and m is a positive integer.
The method according to any one of claims 10 to 14, wherein the generating the processed image according to the equalized output value of each green pixel in the Bayer image to be processed comprises:

For each green pixel in the Bayer format image to be processed, replacing the equalized output value of the green pixel point with the pixel value of the green pixel point;

The processed image is generated according to the respective green pixels after the replacement is completed.