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WO2016019751A1 - Dispositif et procédé de traitement d'image - Google Patents

Dispositif et procédé de traitement d'image Download PDF

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Publication number
WO2016019751A1
WO2016019751A1 PCT/CN2015/080927 CN2015080927W WO2016019751A1 WO 2016019751 A1 WO2016019751 A1 WO 2016019751A1 CN 2015080927 W CN2015080927 W CN 2015080927W WO 2016019751 A1 WO2016019751 A1 WO 2016019751A1
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Prior art keywords
pixel point
value
green
pixel
sliding window
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English (en)
Chinese (zh)
Inventor
李水平
陈玮
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Huawei Technologies Co Ltd
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Huawei Technologies Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise
    • H04N25/68—Noise processing, e.g. detecting, correcting, reducing or removing noise applied to defects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/10—Circuitry of solid-state image sensors [SSIS]; Control thereof for transforming different wavelengths into image signals

Definitions

  • the present invention relates to the field of image processing technologies, and in particular, to an image processing apparatus and method.
  • 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.
  • CCD Charge-coupled Device
  • CMOS Complementary Metal Oxide Semiconductor
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the present invention provides an image processing apparatus and method.
  • the technical solution is as follows:
  • an image processing 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
  • 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 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.
  • 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.
  • 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 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 further includes:
  • 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 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 :
  • 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 :
  • 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 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;
  • n is the number of green samples in the sliding window and m is a positive integer.
  • 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.
  • an image processing method comprising:
  • 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 processed image is generated according to the equalized output values of the respective green pixel points in the Bayer image to be processed.
  • the sliding of the M ⁇ N sliding window in the Bayer format image to be processed includes:
  • the step of reading the pixel value of the central pixel point is performed.
  • the method further includes:
  • 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 calculating a symmetrical value of the pixel value of the central pixel according to the sliding window includes:
  • G 0 ' G1avg+G2avg-G 0 .
  • 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:
  • 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 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:
  • the acquiring the first weight W 1 corresponding to the pixel value G 0 of the central pixel point includes :
  • 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 acquiring the second weight W 2 corresponding to the symmetric value G 0 ′ includes:
  • the mean GDavg is smaller than the first weight W 1 , the mean GDavg is determined as the second weight W 2 ;
  • n is the number of green samples in the sliding window and m is a positive integer.
  • the equalized output value of each green pixel in the Bayer image generates a processed image, including:
  • the processed image is generated according to the respective green pixels after the replacement is completed.
  • 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.
  • 1 is a schematic diagram of a 5 ⁇ 5 Bayer array involved in the background art
  • FIG. 2 is a schematic structural diagram of an image processing apparatus according to an embodiment of the present invention.
  • FIG. 3 is a schematic structural diagram of an image processing apparatus according to another embodiment of the present invention.
  • FIG. 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. 6 is a flowchart of a method for processing an image according to another embodiment of the present invention.
  • 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.
  • 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.
  • FIG. 2 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.
  • the image processing apparatus 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.
  • FIG. 3 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.
  • 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 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.
  • 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 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.
  • 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.
  • 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 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 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 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.
  • 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 :
  • 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 '.
  • 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 .
  • n is the number of green samples in the sliding window and m is a positive integer.
  • 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 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.
  • 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.
  • the device further includes: a difference calculation module 232 and a difference detection module 234.
  • 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 .
  • the image processing apparatus 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.
  • 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.
  • 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.
  • 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.
  • FIG. 4 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.
  • the electronic device 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.
  • 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.
  • 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.
  • 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;
  • G 0 ' G1avg+G2avg-G 0 .
  • 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 .
  • 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:
  • 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 :
  • 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 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 ;
  • n is the number of green samples in the sliding window and m is a positive integer.
  • 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.
  • 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.
  • FIG. 5 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.
  • the image processing method 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.
  • the equalized output value of the central pixel point determines 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.
  • FIG. 6A 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.
  • 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.
  • 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.
  • this step may include the following sub-steps:
  • 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.
  • the image processing method 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.
  • the processed pixel 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.
  • 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.
  • the pixel values of the respective pixel points in the 5 ⁇ 5 sliding window 62 are as shown in Fig. 6C.
  • 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
  • the red pixel point R of the second row and the first column is The pixel value is D 10
  • 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.
  • this step may include the following sub-steps:
  • the first sample mean G1avg of the green pixel on the Gr channel in the sliding window is obtained.
  • 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.
  • the second sample mean G2avg of the green pixel on the Gb channel in the sliding window is obtained.
  • 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.
  • 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 .
  • Step 604 calculating an absolute difference Gdiff of the first sample mean G1avg and the second sample mean G2avg.
  • the absolute difference Gdiff
  • Step 605 Detect whether the absolute difference Gdiff is less than a predetermined threshold value THR.
  • 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.
  • 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.
  • 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.
  • this step may include the following sub-steps:
  • the first weight W 1 corresponding to the pixel value G 0 of the central pixel is obtained.
  • 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.
  • 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.
  • 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.
  • 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.
  • m is the number of green samples in the sliding window and m is a positive integer.
  • the first weight W 1 is determined as the second weight W 2 .
  • the mean GDavg is less than the first weight W 1 , the mean GDavg is determined as the second weight W 2 .
  • 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 ':
  • 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.
  • 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.
  • this step may include the following sub-steps:
  • the equalized output value of the green pixel is replaced by the pixel value of the green pixel.
  • the processed image is generated according to each green pixel after the replacement is completed.
  • 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.
  • the image processing method 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.
  • 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.
  • 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.

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Abstract

L'invention concerne un dispositif et un procédé de traitement d'image qui se rapportent au domaine technique du traitement de l'image. Le dispositif comporte : un module de glissement pour glisser dans une image de format de Bayer à traiter à l'aide d'une fenêtre de glissement M x N; un module de lecture pour lire une valeur de pixel d'un point de pixel central lorsque le point de pixel central dans la fenêtre de glissement est un point de pixel vert; un module de calcul pour calculer une valeur symétrique de la valeur de pixel du point de pixel central selon la fenêtre de glissement; un module de détermination pour déterminer une valeur de sortie d'équilibre du point de pixel central selon la valeur de pixel et la valeur symétrique du point de pixel central; un module de génération pour générer une image traitée selon la valeur de sortie d'équilibre de chaque point de pixel vert dans l'image de Bayer à traiter. Le problème existant dans l'état antérieur de la technique, selon lequel des bruits existent dans une image en raison d'une diaphonie entre des points de pixel adjacents dans une image de format de Bayer obtenue par l'intermédiaire d'un filtrage de matrice de Bayer, est résolu; l'influence de la diaphonie entre les points de pixel adjacents dans l'image est réduite, et l'effet d'affichage d'image est amélioré.
PCT/CN2015/080927 2014-08-07 2015-06-05 Dispositif et procédé de traitement d'image Ceased WO2016019751A1 (fr)

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