WO2016165357A1 - 一种图像处理方法及装置、终端、存储介质 - Google Patents

一种图像处理方法及装置、终端、存储介质 Download PDF

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WO2016165357A1
WO2016165357A1 PCT/CN2015/096808 CN2015096808W WO2016165357A1 WO 2016165357 A1 WO2016165357 A1 WO 2016165357A1 CN 2015096808 W CN2015096808 W CN 2015096808W WO 2016165357 A1 WO2016165357 A1 WO 2016165357A1
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matrix
image
bit
value
processed
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French (fr)
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盛雪飞
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Sanechips Technology Co Ltd
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ZTE Microelectronics Technology Co Ltd
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    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G5/00—Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators
    • G09G5/02—Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators characterised by the way in which colour is displayed

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  • the present invention relates to image processing technologies, and in particular, to an image processing method and apparatus, a terminal, and a storage medium.
  • the dithering algorithm is mainly applied to a digital terminal, wherein the digital terminal includes a set top box, a personal computer, a digital television, a notebook computer, a tablet computer, a mobile phone, a car television, and the like, when the color depth of the video source is greater than the color depth of the display device. It is necessary to perform some processing on the low bit (bit) of each color component.
  • the prior art includes two processing modes, the first processing method is to cut off the low bit, and the second processing method is to use the jitter algorithm for processing. If the first processing method is adopted and the low bits are directly cut off, the image displayed in the terminal will have a light band phenomenon, thereby affecting the effect of people viewing the image.
  • the terminal can reduce the optical band phenomenon during the process of displaying the image, the image displayed by the terminal deviates from the video source to a greater extent, that is, the jitter The algorithm will cause distortion of the original image.
  • the embodiment of the present invention provides an image processing method and apparatus, a terminal, and a storage medium to solve the at least one problem existing in the prior art, and can maintain the display effect of the original image while eliminating the optical band phenomenon.
  • an embodiment of the present invention provides an image processing method, where the method includes:
  • Bayer is determined according to the difference between the color depth X bit of the image to be processed and the color depth Y bit of the display device. a matrix, wherein X is an integer greater than Y, and Z represents a difference in color depth;
  • the preset value and the sum St of the element values in the matrix Pt(i, j) are processed according to a preset operation relationship to obtain Kt, wherein the operation relationship includes a rounding operation;
  • the element value in the matrix Bt(i,j) is corrected by the Kt, and the corrected element value is used as the pixel value of the corresponding pixel on the image to be processed.
  • an embodiment of the present invention provides an image processing apparatus, where the apparatus includes a determining unit, a dividing unit, an assigning unit, a processing unit, and a correcting unit, where:
  • the determining unit is configured to determine a Bayer matrix according to a difference Z bit between a color depth X bit of the image to be processed and a color depth Y bit of the image processing device, where X is an integer greater than Y, and Z represents a difference in color depth;
  • the dividing unit is configured to divide the image to be processed according to the Bayer matrix to obtain Q image blocks;
  • the evaluation unit is configured to assign a pixel value represented by a Y bit of the tth image block in the Q image blocks to a matrix Bt(i, j), and assign a pixel value represented by the Z bit to the matrix Pt(i,j), where 1 ⁇ t ⁇ Q, 1 ⁇ i ⁇ N,1 ⁇ j ⁇ N;
  • the processing unit is configured to process the preset value and the sum St of the element values in the matrix Pt(i, j) according to a preset operation relationship to obtain Kt, wherein the operation relationship includes a rounding operation;
  • the correcting unit is configured to correct the element value in the matrix Bt(i, j) by using the Kt, and use the corrected element value as the pixel value of the corresponding pixel on the image to be processed.
  • an embodiment of the present invention provides a terminal, where the terminal includes a processor and a display device, where:
  • a processor configured to determine a Bayer matrix according to a difference Z of a color depth X bit of the image to be processed and a color depth Y bit of the display device, wherein X is an integer greater than Y, and Z represents a difference in color depth;
  • the preset value and the sum St of the element values in the matrix Pt(i, j) are processed according to a preset operation relationship to obtain Kt, wherein the operation relationship includes a rounding operation;
  • a display device configured to display an image processed by the processor, the color depth of the display device being Y.
  • an embodiment of the present invention provides a computer storage medium, where the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute an image processing method provided by the first aspect of the present invention.
  • a Bayer matrix is determined according to a difference Z position between a color depth X bit of an image to be processed and a color depth Y bit of a display device;
  • the matrix divides the image to be processed to obtain Q image blocks; assigns pixel values represented by Y bits of the t-th image block in the Q image blocks to the matrix Bt(i, j), and sets Z
  • the pixel value represented by the bit is assigned to the matrix Pt(i,j); the preset value and the sum St of the element values in the matrix Pt(i,j) are processed according to a preset operational relationship to obtain Kt, where
  • the operation relationship includes a rounding operation; correcting an element value in the matrix Bt(i, j) by using the Kt, and using the corrected element value as a pixel value of a corresponding pixel on the image to be processed; It can maintain the original image display while eliminating the band phenomenon.
  • 1 is a display device lacking a 1-bit corresponding Bayer matrix
  • 2 is a display device lacking a 2-bit corresponding Bayer matrix
  • 3 is a display device lacking a 3-bit corresponding Bayer matrix
  • 4 is a display device lacking a 4-bit corresponding Bayer matrix
  • FIG. 5 is a schematic flowchart of an implementation process of an image processing method according to an embodiment of the present invention.
  • FIG. 6 is a schematic flowchart of an implementation process of an image processing method according to Embodiment 2 of the present invention.
  • FIG. 7 is a schematic diagram of Pt(i, j) according to Embodiment 2 of the present invention.
  • 8-1 is a schematic structural diagram of a structure of an image processing apparatus according to Embodiment 3 of the present invention.
  • FIG. 8-2 is a schematic structural diagram of a modification unit according to Embodiment 3 of the present invention.
  • an improved dithering algorithm is proposed, which can eliminate the optical band phenomenon while maintaining the display effect of the original image.
  • the dithering algorithm is divided into space dithering algorithm and time dithering algorithm according to the space-time relationship.
  • the time dithering algorithm needs to occupy a lot of resources in hardware implementation, but the space occupied is relatively small.
  • Embodiments of the present invention provide an improved spatial dithering algorithm applied to the field of image processing.
  • the spatial dithering algorithm is a matrix dithering algorithm based on a Bayer table.
  • the embodiment of the present invention effectively utilizes a feature of the Bayer table to achieve better processing of image jitter.
  • the characteristics of the Bayer table are as follows:
  • Figure 1 shows a 1-bit Bayer matrix where 0 and 0 are diagonal positions; 1 and 1 are diagonal positions.
  • Figure 2 shows a 2-bit Bayer matrix where 0 and 1 are object positions and 2 and 3 are diagonal positions.
  • Figure 3 shows a 3-bit Bayer matrix with the same number of positions.
  • the element value in Figure 3 is 0.
  • the two positions are located at (1,1) and (3,3), respectively, where the first number x in (x,y) represents the number of lines, ()
  • the second number y represents the number of columns, and the elements in the matrix with an element value of 0 are separated.
  • the element value in Figure 3 is 4 and the two positions are located at (1, 2) and (3, 4) respectively.
  • the elements with an element value of 4 in the visible matrix are also separated.
  • Units, the same reason, in Figure 3, the two elements with the element values 1, 5, 6, 2, 7, 3 are all apart. Units, located far away.
  • Figure 4 shows a 4-bit Bayer matrix in which the 4-bit Bayer matrix is represented in hexadecimal, 0 and 1, 2 and 3, 4 and 5, 6 and 7, 8 and 9, A and B, C and Among the 8 pairs of elements D, E and F, the distance between the two numbers is Units.
  • the Bayer matrix has a property that when the Bayer matrix (see Figure 1 and Figure 3) has two elements of the same element value, the distance between the two elements is farther; when the Bayer matrix (see Figure 2 and In Figure 4), there are two elements of the same element value. The two elements adjacent to the element value are far apart and regular.
  • the value of a certain number of adjacent elements in the 4Mn region should be in 4Mn+Un or 4Mn+3Un, not in the 4Mn region; a certain number of adjacent elements in the 4Mn+Un region
  • the value should be 4Mn or 4Mn+2Un, not in the 4Mn+Un region; the value of a certain number of adjacent elements in the 4Mn+2Un region should be 4Mn+Un or 4Mn+3Un, not in the 4Mn+2Un region;
  • the value of a certain number of adjacent elements in the 4Mn+3Un region should be in 4Mn or 4Mn+2Un, not in the 4Mn+3Un region. That is, the element values n+1 and n-1 of a certain element value n in the Bayer matrix (the element value exists only when n is greater than 1) are not close to n, and the distance has Regularity.
  • the above regularity can be applied to the dithering algorithm, and the video source is added to the lower value of the display device, and the result is obtained by dividing the total number of pixels in the overall matrix.
  • the results are added to the pixels of the truncated lower bits in order from the smallest to the largest or from the largest to the smallest in the order of the numbers in the Bayer matrix.
  • This method has two advantages. One advantage is due to the characteristics of the Bayer matrix introduced above, that is, the distance between adjacent two numbers is relatively long, so that the pixel points added by 1 are far away from each other, so no noise occurs.
  • the second advantage is that compared to other dithering algorithms, the number of 1s added is the first few bits of the sum of the low-order values to be removed by the video source, closer to the video source.
  • An embodiment of the present invention provides an image processing method, which is applied to a terminal.
  • the function implemented by the image processing method can be implemented by using a processor in a terminal to call a program code.
  • the program code can be saved in a computer storage medium.
  • the terminal includes at least a processor and a storage medium.
  • FIG. 5 is a schematic flowchart of an implementation of an image processing method according to an embodiment of the present invention. As shown in FIG. 5, the method may include:
  • Step 501 Determine a Bayer matrix according to a difference Z position between a color depth X bit of the image to be processed and a color depth Y bit of the display device, where X is an integer greater than Y, Z represents a difference in color depth, and the Bayer matrix is N ⁇ N square matrix;
  • the dithering algorithm is to process the Z bit to be reduced for each pixel, and to compensate for the truncated image. This processing is generally referred to as Z bit jitter.
  • Z may be any integer greater than 0, and has a corresponding Bayer matrix corresponding thereto.
  • the Z bit is 1 bit, 2 bit, 3 bit, and 4 bit, and the Z bit is 1 bit as shown in FIG. 1 .
  • FIG. 2 shows a Bayer matrix when the Z bit is 2 bits
  • FIG. 3 shows a Bayer matrix when the Z bit is 3 bits
  • FIG. 4 shows a Bayer matrix when the Z bit is 4 bits.
  • Step 502 dividing the image to be processed according to the Bayer matrix to obtain Q image blocks.
  • Step 503 Assign a pixel value represented by a Y bit of the tth image block in the Q image blocks to a matrix Bt(i, j), and display a pixel value represented by remaining Z bits of the tth image block. Assigned to the matrix Pt(i,j), where 1 ⁇ t ⁇ Q,1 ⁇ i ⁇ N,1 ⁇ j ⁇ N;
  • Step 504 The preset value and the sum St of the element values in the matrix Pt(i, j) are processed according to a preset operation relationship to obtain Kt, wherein the operation relationship includes a rounding operation, and Kt is an integer. Kt is used to correct the pixel values in Bt(i,j).
  • the preset value may be a sum of pixels in the tth image block; the preset value and a sum of element values in the matrix Pt(i, j) According to the preset operation relationship, Kt is obtained, including:
  • the sum of the element values St in the matrix Pt(i,j) corresponding to the t-th image block is divided by the sum of the number of pixels in the t-th image block, and rounded down to obtain Kt.
  • Step 505 using the Kt to correct the element value in Bt(i, j), and using the corrected element value as the pixel value of the corresponding pixel on the image to be processed.
  • step 505 the element value in Bt(i,j) is corrected by using the Kt, and Using the corrected element value as the pixel value of the corresponding pixel on the image to be processed, including:
  • Step 5051 For Bt(i,j) corresponding to the tth image block, select Kt elements from the Bayer matrix according to the order of the element values in the Bayer matrix from small to large or from large to small;
  • Step 5052 adding 1 to the element value corresponding to the Kt element in the Bt(i,j) to obtain a matrix Rt(i,j);
  • Step 5053 determining whether Rt(i,j) overflows. If Rt(i,j) overflows, the final output value Rt-output(i,j) of the pixel (i,j) in the image to be processed is output terminal The maximum value that the display device can display is 2 Y ; otherwise, the final output value Rt-output(i,j) of the pixel (i,j) in the image to be processed is Rt(i,j).
  • the element value of the Kt element in the Bayer matrix corresponds to two or more elements
  • one of them is selected as the Kt.
  • the above method selects elements from the t-th image block in the order of element values, and may have two or more elements corresponding to the same element value, and may arbitrarily select one.
  • the pixel value represented by the Y bit of the tth image block in the Q image blocks is assigned to the matrix Bt(i, j), and the remaining Z of the tth image block is assigned to the matrix Pt(i,j), including:
  • the pixel value represented by the high Y bit of the tth image block is assigned to the matrix Bt(i,j), and the pixel value represented by the low Z bit of the tth image block is assigned to the matrix Pt(i,j).
  • the color depth may also be referred to as a color bit depth, which is a unit for indicating the number of colors of the terminal by the number of bits, where bit is a binary unit (or bit) calculated by a computer.
  • the color depth is represented by a power exponent of 2. The higher the bit number, the higher the color depth value, and the more colors the image can represent.
  • the 1bit image is 2 to the 1st power and can only be expressed in black and white.
  • the 2bit image is 2 squares that can represent 4 colors, so in addition to black and white, you can also express two gray tones between them.
  • the 24-bit image can display 16,777,216 colors, which are very close to the color that can be distinguished by the naked eye, so it is called True color.
  • the 24-bit color depth has become the most basic requirement of color scanners, and the highest has reached 36bit or 48bit.
  • the image uses color space on the terminal device (also known as color model, also known as color space or color Color system) to indicate that the current mainstream color space mainly includes RGB color space, CMY color space, HSV color space and Lab color space, wherein: RGB color space is defined by the color recognized by the human eye, which can represent large Part of the color, where R (Red) means red, G (Green) means green, and B (Blue) means blue.
  • CMY is a color space used in industrial printing, which corresponds to the RGB color space, where C (Cyan) represents cyan, M (Magenta) represents magenta, and Y (Yellow) represents yellow.
  • the HSV color space is a color space created by A.R.
  • H Hue
  • S saturation
  • V Value
  • L*a*b color space is used for computer tone adjustment and color correction, which is independent of the device's color model.
  • RGB color space when the image is represented by the RGB color space, the image is represented by three dimensions R, G, and B, where each dimension R, G, and B is A color component, although the RGB color space is taken as an example, the meaning of the color component is also applicable to other color spaces such as the CMY color space.
  • the Bayer matrix is determined according to the Z bit of the color depth X bit of the image to be processed and the color depth Y bit of the display device; the image to be processed is divided according to the Bayer matrix to obtain Q image blocks. Placing a pixel value represented by a Y bit of the tth image block in the Q image block to a matrix Bt(i,j), and assigning a pixel value represented by the remaining Z bits of the tth image block Giving a matrix Pt(i,j); processing the preset value and the sum St of the element values in the matrix Pt(i,j) according to a preset operational relationship to obtain Kt, where Kt is an integer; using the Kt Correcting the element value in Bt(i, j), and using the corrected element value as the pixel value of the corresponding pixel on the image to be processed; thus, the display of the original image can be maintained while eliminating the band phenomenon effect.
  • An embodiment of the present invention provides an image processing method, which is applied to a terminal.
  • the function implemented by the image processing method can be implemented by using a processor in a terminal to call a program code.
  • the code can be stored in a computer storage medium.
  • the terminal includes at least a processor and a storage medium.
  • FIG. 6 is a schematic flowchart of an implementation of an image processing method according to Embodiment 2 of the present invention. As shown in FIG. 6, the method may include:
  • Step 601 Calculate a difference between a color depth of the video source and a color depth of the display device on the terminal, and select a Bayer matrix according to the difference between the color depths.
  • the color depth (bit width) of the three color components of R, G, and B is 8 bits, and if the 8-bit video source (the image to be processed) is to be displayed, R, G, and B are 5 bits, respectively.
  • the R color components need to be 3 jitters respectively, that is, the Bayer matrix corresponding to 3 bits needs to be selected;
  • the G color components need to perform 2 bit jitter respectively, that is, the Bayer matrix corresponding to 2 bits needs to be selected;
  • B color The components need to be 3 bits of jitter, that is, the Bayer matrix corresponding to 3 bits needs to be selected.
  • the color depth of the video source is X bit
  • the color depth of the display device of the terminal is Y bit
  • Z XY
  • the number of bits to be reduced is displayed on the display device of the terminal.
  • the dithering algorithm is to process the Z bit to be reduced for each pixel, and to compensate for the truncated image. This processing is generally referred to as Z bit jitter.
  • Z may be any integer greater than 0, and has a corresponding Bayer matrix corresponding thereto.
  • the Z bit is 1 bit, 2 bit, 3 bit, and 4 bit, and the Z bit is 1 bit as shown in FIG. 1 .
  • FIG. 2 shows a Bayer matrix when the Z bit is 2 bits
  • FIG. 3 shows a Bayer matrix when the Z bit is 3 bits
  • FIG. 4 shows a Bayer matrix when the Z bit is 4 bits.
  • Step 602 dividing the sum of the values of the pixels in the Bayer matrix by the total number of pixels in the matrix, and rounding down to obtain the result Kt.
  • step 602 is:
  • Step 6021 dividing the image into Q maps according to the Bayer matrix selected in step S201.
  • the pixel points in each of the Q image blocks are in one-to-one correspondence with the elements in the Bayer matrix.
  • the image block also includes N ⁇ N pixels.
  • Step 6022 For the t-th image block, add the values (pixel values) corresponding to the low Z bit of the pixels in the t-th image block to obtain St, where t is an integer greater than or equal to 1 and less than or equal to Q.
  • this Bayer matrix block is an N ⁇ N size matrix block, and for the tth image block, St can be calculated by the formula (2):
  • i a horizontal direction dimension
  • j a vertical direction dimension
  • X bit a total pixel value (X bit) of a pixel (i, j) corresponding to a Bayer matrix block
  • the pixel value of the high Y bit of the pixel (i, j) is Bt(i, j)
  • Pt(i, j) of the low Z bit of the pixel (i, j) where, high Y
  • the pixel value of the bit Bt(i,j) is actually the pixel value after the image to be processed is truncated (hereinafter referred to as the truncated pixel value), and the pixel value Bt(i,j) after the truncation and the total pixel
  • Equation (3) the relationship between the values At(i,j) can be expressed by equation (3):
  • the total pixel value At(i, j) divided by the power of Z of 2 is the truncated pixel value Bt(i, j), and Z represents the difference in color depth.
  • Step 6023 for the tth image block, divide St by the total number of pixels L in the Bayer matrix, and round down to obtain Kt.
  • Kt can be calculated using equation (4):
  • the Bayer matrix corresponding to the jitter of 3 bits is 4 ⁇ 4 (see FIG. 3), that is, N is 4, and the image to be processed is divided from left to right and from top to bottom.
  • N is 4, and the image to be processed is divided from left to right and from top to bottom.
  • the image to be processed that is, the image input to the embodiment of the present invention, in other words, can be understood as an image of the video source; in the process of dividing the image to be processed by the Bayer matrix, there may be cases where the image cannot be properly divided.
  • the technical solutions provided by the embodiments of the present invention are also applicable to the case where they cannot be properly divided.
  • the block of 4 ⁇ 4 in the above example also adds the pixel values of the lower 3 bits, and divides the total number of pixels in the image block to obtain the Kt of the image block.
  • Step 603 selecting Kt elements from the Bayer matrix according to the order of the element values in the Bayer matrix from small to large or from large to small; adding 1 to the truncated pixel value corresponding to the Kt elements, see formula (5):
  • the Kt obtained in the step S202 is 3, where the order of the elements in the Bayer matrix is as small as possible to illustrate the selection of elements from the Bayer matrix.
  • the Bayer matrix selects three elements in total, including two elements with an element value of 0 and an element with an element value of 1, and then adds 1 to the pixel value of the two elements with a value of 0 in the Bayer matrix. Then the element value is 1 in the Bayer matrix. Add one to the two pixel values corresponding to the two elements.
  • an image is processed using a 3-bit dither matrix and the remaining 3 ⁇ 4 image blocks on the right are found.
  • the upper left corner of the image block corresponds to the upper left corner of the matrix in Figure 3, and the first three columns are used.
  • the latter processing method is the same as that of the 4 ⁇ 4 block.
  • the order from small to large is taken as an example, and the pixel corresponding to the small number in the matrix is preferentially incremented by one; if the number is the same, one is selected arbitrarily.
  • step 603 although the order is as small as possible, it should be understood by those skilled in the art that the order from 603 can also be used in the step 603, in order to save space and look. Concise, so I won't go into details.
  • Step 604 determining whether Rt(i,j) overflows. If Rt(i,j) overflows, the final output value of the pixel (i,j) Rt-output(i,j) is the maximum display device of the output terminal. The value 2 Y , conversely, the final output value Rt-output(i,j) of the pixel (i,j) is Rt(i,j).
  • the pixel value of the display device output pixel point (i, j) of the terminal is the maximum value (2 Y ) that the display device of the terminal can display; otherwise, the output Rt(i, j).
  • the determining unit, the dividing unit, the assigning unit, the processing unit, the correcting unit, and the correcting unit in the image processing apparatus provided by the embodiment of the present invention are based on the foregoing method embodiments.
  • the module can be implemented by a processor in the terminal; of course, it can also be implemented by a specific logic circuit; in the process of the specific embodiment, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal. Processor (DSP) or field programmable gate array (FPGA).
  • CPU central processing unit
  • MPU microprocessor
  • DSP digital signal. Processor
  • FPGA field programmable gate array
  • the image processing apparatus 800 includes a determining unit 801, a dividing unit 802, an assigning unit 803, a processing unit 804, and a correcting unit. 805, where:
  • the determining unit 801 is configured to determine a Bayer matrix according to a difference Z bit between a color depth X bit of the image to be processed and a color depth Y bit of the image processing device, where X is an integer greater than Y, and Z represents a difference in color depth,
  • the Bayer matrix is an N ⁇ N square matrix;
  • the dividing unit 802 is configured to divide the to-be-processed image according to the Bayer matrix to obtain Q image blocks;
  • the evaluation unit 803 is configured to assign a pixel value represented by a Y bit of the tth image block in the Q image blocks to a matrix Bt(i, j), and to leave a remaining Z of the tth image block
  • the pixel value represented by the bit is assigned to the matrix Pt(i,j), where 1 ⁇ t ⁇ Q, 1 ⁇ i ⁇ N,1 ⁇ j ⁇ N;
  • the processing unit 804 is configured to process the preset value and the sum St of the element values in the matrix Pt(i, j) corresponding to the t-th image block according to a preset operation relationship to obtain Kt, where Kt is an integer
  • Kt is used to correct pixel values in Bt(i,j);
  • the correcting unit 805 is configured to correct the element value in the Bt(i, j) by using the Kt, and use the corrected element value as the pixel value of the corresponding pixel on the image to be processed.
  • the preset value is a sum of the number of pixels in the tth image block; the processing unit is configured to be in a matrix Pt(i, j) corresponding to the tth image block.
  • the sum of the element values St is divided by the sum of the number of pixels in the t-th image block, and rounded down to obtain Kt.
  • the modification unit 805 includes a selection module 8051, an operation module 8052, and an output module 8053, where:
  • the selection module 8051 is configured to press Bt(i,j) corresponding to the tth image block. Selecting Kt elements from the Bayer matrix in the order of the element values in the Bayer matrix from small to large or from large to small;
  • the operation module 8052 is configured to add 1 to the element value corresponding to the Kt elements in the Bt(i,j) to obtain a matrix Rt(i,j);
  • the output module 8053 is configured to determine whether Rt(i,j) overflows, and if Rt(i,j) overflows, the final output value of the pixel (i,j) in the image to be processed is Rt-output(i,j) ) is the maximum value 2 Y that the display device of the output terminal can display; conversely, the final output value Rt-output(i, j) of the pixel (i, j) in the image to be processed is Rt(i, j).
  • the selection module is further configured to follow the order of the element values in the Bayer matrix from small to large or from large to small.
  • the element values of the Kt elements in the Bayer matrix correspond to more than two elements, Choose one of them as the Kt element.
  • the evaluation unit is configured to assign a pixel value represented by a high Y bit of the tth image block to the matrix Bt(i, j), and represent the low Z bit of the tth image block.
  • the pixel values are assigned to the matrix Pt(i,j).
  • the image processing method described above is implemented in the form of a software function module and sold or used as a stand-alone product, it may also be stored in a computer readable storage medium.
  • the technical solution of the embodiments of the present invention may be embodied in the form of a software product in essence or in the form of a software product stored in a storage medium, including a plurality of instructions. Enabling a computer device (which may be a personal computer, server, or network device, etc.) to perform various embodiments of the present invention All or part of the method.
  • the foregoing storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read only memory (ROM), a magnetic disk, or an optical disk.
  • program codes such as a USB flash drive, a mobile hard disk, a read only memory (ROM), a magnetic disk, or an optical disk.
  • the embodiment of the present invention further provides a computer storage medium, where the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute an image processing method in the embodiment of the present invention.
  • an embodiment of the present invention provides a terminal, where the terminal includes a processor and a display device, where:
  • a processor configured to determine a Bayer matrix according to a difference Z of a color depth X bit of the image to be processed and a color depth Y bit of the display device, wherein X is an integer greater than Y, and Z represents a difference in color depth, the Bayer matrix An N ⁇ N square matrix; dividing the image to be processed according to the Bayer matrix to obtain Q image blocks; assigning pixel values represented by Y bits of the tth image block in the Q image blocks Giving the matrix Bt(i,j) the pixel values represented by the remaining Z bits of the tth image block to the matrix Pt(i,j), where 1 ⁇ t ⁇ Q,1 ⁇ i ⁇ N,1 ⁇ j ⁇ N; the preset value and the sum St of the element values in the matrix Pt(i, j) are processed according to a preset operational relationship to obtain Kt, where Kt is an integer, and the Kt is used for Bt(i) Correcting the pixel value in j); correcting the element value in Bt(i,
  • a display device configured to display an image processed by the processor, the color depth of the display device being Y.
  • the disclosed apparatus and method may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner such as: multiple units or components may be combined, or Can be integrated into another system, or some features can be ignored or not executed.
  • the coupling, or direct coupling, or communication connection of the components shown or discussed may be indirect coupling or communication connection through some interfaces, devices or units, and may be electrical, mechanical or other forms. of.
  • the units described above as separate components may or may not be physically separated, and the components displayed as the unit may or may not be physical units; they may be located in one place or distributed on multiple network units; Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated into one unit;
  • the unit can be implemented in the form of hardware or in the form of hardware plus software functional units.
  • the foregoing program may be stored in a computer readable storage medium, and when executed, the program includes The foregoing steps of the method embodiment; and the foregoing storage medium includes: a removable storage device, a read only memory (ROM), a magnetic disk, or an optical disk, and the like, which can store program codes.
  • ROM read only memory
  • the above-described integrated unit of the present invention may be stored in a computer readable storage medium if it is implemented in the form of a software function module and sold or used as a standalone product.
  • the technical solution of the embodiments of the present invention may be embodied in the form of a software product in essence or in the form of a software product stored in a storage medium, including a plurality of instructions.
  • a computer device (which may be a personal computer, server, or network device, etc.) is caused to perform all or part of the methods described in various embodiments of the present invention.
  • the foregoing storage medium includes various media that can store program codes, such as a mobile storage device, a ROM, a magnetic disk, or an optical disk.
  • the Bayer matrix is determined according to the Z bit of the color depth X bit of the image to be processed and the color depth Y bit of the display device; the image to be processed is divided according to the Bayer matrix to obtain Q image blocks. And assigning the pixel value represented by the Y bit of the tth image block to the matrix Bt(i,j), and assigning the pixel value represented by the remaining Z bits of the tth image block to the matrix Pt(i,j) And processing the preset value and the sum St of the element values in the matrix Pt(i, j) according to a preset operation relationship to obtain Kt, wherein the operation relationship includes a rounding operation, and the Kt is used for the Bt Correcting the pixel value in (i, j); correcting the element value in Bt(i, j) by using the Kt, and using the corrected element value as the pixel value of the corresponding pixel on the image to be processed; It can maintain the original image display while eliminating the band phenomenon.

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Abstract

本发明实施例公开了一种图像处理方法及装置、终端、存储介质，所述方法包括：根据待处理图像的色深X位与显示设备的色深Y位之差Z位确定Bayer矩阵；按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的剩余的Z位所表示的像素值赋值给矩阵Pt(i,j)；将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中所述运算关系包括取整运算；利用所述Kt对Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值。

Description

一种图像处理方法及装置、终端、存储介质 技术领域
本发明涉及图像处理技术，尤其涉及一种图像处理方法及装置、终端、存储介质。
背景技术
抖动算法主要应用于数字终端中，其中，数字终端包括机顶盒、个人计算机、数字电视、笔记本电脑、平板电脑、手机、车载电视等电子设备，在视频源的色深大于显示设备的色深的时候，需要对每个色彩分量多出来的低bit(位)进行一些处理。现有技术中包括两种处理方式，第一种处理方式是将低位截掉，第二种处理方式是采用抖动算法进行处理。如果采用第一种处理方式，直接截掉这些低位，则终端中显示的图像就会出现光带现象，从而影响人们观看图像的效果。如果采用第二种处理方式，采用抖动算法对低位进行处理后，虽然终端在显示图像的过程中可以减轻光带现象，但是终端显示的图像却偏离视频源的程度比较大，也就是说，抖动算法会造成原始图像的失真。
发明内容
有鉴于此，本发明实施例为解决现有技术中存在的至少一个问题而提供一种图像处理方法及装置、终端、存储介质，能够在消除光带现象的同时，保持原始图像的显示效果。
本发明实施例的技术方案是这样实现的：
第一方面，本发明实施例提供一种图像处理方法，所述方法包括：
根据待处理图像的色深X位与显示设备的色深Y位之差Z位确定Bayer 矩阵，其中，X为大于Y的整数，Z表示色深之差；
按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；
将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将Z位所表示的像素值赋值给矩阵Pt(i,j)，其中1≤t≤Q，1≤i≤N，1≤j≤N；
将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中所述运算关系包括取整运算；
利用所述Kt对所述矩阵Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值。
第二方面，本发明实施例提供一种图像处理装置，所述装置包括确定单元、划分单元、赋值单元、处理单元和修正单元，其中：
所述确定单元，配置为根据待处理图像的色深X位与图像处理设备的色深Y位之差Z位确定Bayer矩阵，其中，X为大于Y的整数，Z表示色深之差；
所述划分单元，配置为按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；
所述赋值单元，配置为将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将Z位所表示的像素值赋值给矩阵Pt(i,j)，其中1≤t≤Q，1≤i≤N，1≤j≤N；
所述处理单元，配置为将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中所述运算关系包括取整运算；
所述修正单元，配置为利用所述Kt对所述矩阵Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值。
第三方面，本发明实施例提供一种终端，所述终端包括处理器和显示设备，其中：
处理器，配置为根据待处理图像的色深X位与显示设备的色深Y位之差Z位确定Bayer矩阵，其中，X为大于Y的整数，Z表示色深之差；
按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；
将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将Z位所表示的像素值赋值给矩阵Pt(i,j)，其中1≤t≤Q，1≤i≤N，1≤j≤N；
将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中所述运算关系包括取整运算；
利用所述Kt对Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值；
显示设备，配置为显示经过所述处理器处理过的图像，所述显示设备的色深为Y。
第四方面，本发明实施例提供一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，该计算机可执行指令用于执行本发明第一方面实施例提供的图像处理方法。
本发明实施例提供的一种图像处理方法及装置、终端、存储介质，其中，根据待处理图像的色深X位与显示设备的色深Y位之差Z位确定Bayer矩阵；按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将Z位所表示的像素值赋值给矩阵Pt(i,j)；将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中所述运算关系包括取整运算；利用所述Kt对所述矩阵Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值；如此，能够在消除光带现象的同时，保持原始图像的显示效果。
附图说明
图1是显示设备缺少1bit对应的Bayer矩阵；
图2是显示设备缺少2bit对应的Bayer矩阵；
图3是显示设备缺少3bit对应的Bayer矩阵；
图4是显示设备缺少4bit对应的Bayer矩阵；
图5为本发明实施例一图像处理方法的实现流程示意图；
图6为本发明实施例二图像处理方法的实现流程示意图；
图7为本发明实施例二中Pt(i,j)的示意图；
图8-1为本发明实施例三图像处理装置的组成结构示意图；
图8-2为本发明实施例三中修正单元的组成结构示意图。
具体实施方式
本发明实施例为解决现有技术抖动算法存在的失真问题，将提出一种改进的抖动算法，能够在消除光带现象的同时，保持原始图像的显示效果。在对本发明实施例的技术方案阐述之前，先对抖动算法进行描述。抖动算法按时空关系分为空间抖动算法和时间抖动算法两类，其中时间抖动算法在硬件实现上需要占用很多资源，但是占用的空间相对较少。本发明实施例将提供一种改进的空间抖动算法应用于图像处理领域，具体来说该空间抖动算法是一种基于Bayer表的矩阵抖动算法。
本发明实施例有效利用了Bayer表的一个特性，来实现对图像抖动的更优处理，Bayer表的特性介绍如下：
图1所示的是1bit的Bayer矩阵，其中，0与0是对角位置；1与1是对角位置。
图2所示的是2bit的Bayer矩阵，其中，0和1是对象位置，2与3是对角位置。
图3所示的是3bit的Bayer矩阵，相同数字的位置都是
Figure PCTCN2015096808-appb-000001
个单位，例如，图3中的元素值为0两个位置分别位于(1,1)和(3，3)，其中(x，y)中的第一个数字x表示行数，()中的第二个数字y表示列数，可见矩阵中元素值为0的元素相距
Figure PCTCN2015096808-appb-000002
个单位；再如，图3中的元素值为4两个位置分别位于(1,2)和(3，4)，可见矩阵中元素值为4的元素也相距
Figure PCTCN2015096808-appb-000003
个单位，同理，在图3中元素值为1、5、6、2、7、3的两个元素都是相距
Figure PCTCN2015096808-appb-000004
个单位，位置较远。
图4所示的是4bit的Bayer矩阵，其中，4bit的Bayer矩阵采用十六进制表示，0和1，2和3，4和5，6和7，8和9，A和B，C和D，E和F这8对元素中，相互两个数字的距离是
Figure PCTCN2015096808-appb-000005
个单位。
综合说来，Bayer矩阵有个特性，当Bayer矩阵(参见图1和图3)中存在相同的元素值的两个元素时，这两个元素的距离比较远；当Bayer矩阵(参见图2和图4)中不存在相同的元素值的两个元素，元素值相邻的两个元素的距离较远，而且很规律。
上面示出的Bayer矩阵是直观的元素值，下面再从Bayer矩阵的公式演绎一下，Bayer矩阵的公式如公式(1)所示：
Figure PCTCN2015096808-appb-000006
从公式(1)可以看出，4Mn区域中某个数相邻的元素值应该在4Mn+Un或4Mn+3Un中，不会在4Mn区域中；4Mn+Un区域中某个数相邻的元素值应该在4Mn或4Mn+2Un，不会在4Mn+Un区域中；4Mn+2Un区域中某个数相邻的元素值应该在4Mn+Un或4Mn+3Un，不会在4Mn+2Un区域中；4Mn+3Un区域中某个数相邻的元素值应该在4Mn或4Mn+2Un中，不会在4Mn+3Un区域中。即，Bayer矩阵中某个元素值n相近的元素值n+1和n-1(该元素值只在n大于1的时候存在)不会离n很近，而且这种距离具有 规律性。
上述的规律性可以应用到抖动算法中，把视频源多出显示设备的低位数值加起来，除以整体矩阵中的像素总数得到结果。把结果按照Bayer矩阵中数的顺序，从小到大或从大到小依次给各个截掉低位的像素点加1。这种方法有两个优点，一个优点得益于上面介绍的Bayer矩阵的特性，即相邻两个数字距离比较远，这样加1的像素点距离较远不会集中，所以不会出现噪点；第二个优点是，相比其它抖动算法，加的1的个数是视频源要去掉的低位数值的总和的前几比特，更贴近视频源。
下面结合附图和具体实施例对本发明的技术方案进一步详细阐述。
实施例一
本发明实施例提供一种图像处理方法，应用于终端，该图像处理方法所实现的功能可以通过终端中的处理器调用程序代码来实现，当然程序代码可以保存在计算机存储介质中，可见，该终端至少包括处理器和存储介质。
图5为本发明实施例一图像处理方法的实现流程示意图，如图5所示，该方法可以包括：
步骤501，根据待处理图像的色深X位与显示设备的色深Y位之差Z位确定Bayer矩阵，其中，X为大于Y的整数，Z表示色深之差，所述Bayer矩阵为N×N方阵；
这里，步骤501包括：计算待处理图像的色深X位与显示设备的色深Y位之差，根据色深之差Z＝X-Y选择一种Bayer矩阵；在具体实现的过程中，也可以预设一个关系列表，该关系列表用于表明色深之差Z与Bayer矩阵之间映射关系，因此，上述步骤根据色深之差Z＝X-Y查询预设的关系列表，然后选择一种Bayer矩阵。
举例来说，假设对于某个颜色分量(又称为色彩分量)，视频源的色深 是X bit，终端的显示设备的色深是Y bit，当Y<X时，令Z＝X-Y，Z就是视频源在终端的显示设备上显示将要减少的位数(简称截位)。抖动算法就是要对每个像素要减少的Z bit做处理，补偿在截位后的图像上，一般把这种处理称为Z bit的抖动。对于Z bit的抖动，需要选择与Z bit对应的Bayer矩阵。Z可以是大于0的任意整数，都有相应的Bayer矩阵与之对应，本发明实施例中以Z bit为1bit、2bit、3bit和4bit为例，其中，图1所示的是Z bit为1bit时的Bayer矩阵，图2所示的是Z bit为2bit时的Bayer矩阵，图3所示的是Z bit为3bit时的Bayer矩阵，图4所示的是Z bit为4bit时的Bayer矩阵。
步骤502，按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；
步骤503，将所述Q个图像块中第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的剩余的Z位所表示的像素值赋值给矩阵Pt(i,j)，其中1≤t≤Q，1≤i≤N，1≤j≤N；
步骤504，将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中所述运算关系包括取整运算，Kt为整数，所述Kt用于对Bt(i,j)中像素值进行修正。
这里，在具体实施的过程中，所述预设数值可以为所述第t个图像块中像素之和；所述将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，包括：
将第t个图像块所对应的矩阵Pt(i,j)中元素值之和St除以所述第t个图像块中像素个数之和，并向下取整进行处理得到Kt。
步骤505，利用所述Kt对Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值。
这里，步骤505，所述利用所述Kt对Bt(i,j)中的元素值进行修正，并 将修正后的元素值作为所述待处理图像上对应像素的像素值，包括：
步骤5051，对于与第t个图像块相对应的Bt(i,j)，按照Bayer矩阵中元素值从小到大或从大到小的顺序从Bayer矩阵选择Kt个元素；
步骤5052，将所述Bt(i,j)中与所述Kt个元素对应的元素值加1，得到矩阵Rt(i,j)；
步骤5053，判断Rt(i,j)是否溢出，如果Rt(i,j)溢出，所述待处理图像中像素(i,j)最终的输出值Rt-output(i,j)为输出终端的显示设备能显示的最大值2Y；反之，所述待处理图像中像素(i,j)最终的输出值Rt-output(i,j)为Rt(i,j)。
本发明实施例中，按照Bayer矩阵中元素值从小到大或从大到小的顺序，当Bayer矩阵中第Kt个元素的元素值对应两个以上的元素时，任选其中之一作为第Kt个元素。例如一，假设Kt＝2且按照从大到小的顺序，即一共要根据Bayer矩阵从第t个图像块中选择Kt＝2个元素，假设元素值中的最大值为4，而该最大值4对应有三个元素，那么从三个元素中任意选择Kt＝2个元素即可。进一步地，假设在选择Kt＝2中第一个元素时，从元素值为4的三个元素中任意选择一个元素作为Kt＝2中第一个元素；然后再选择Kt＝2中第二个元素时，那么在本例中，第Kt＝2个元素的元素值仍为4，而再选择完Kt＝2中第一个元素后，元素值4还对应有两个元素，那么从元素值为4的两个元素中任意选择一个作为第Kt个元素。至此，本例已经根据Bayer矩阵从第t个图像块中选择出Kt＝2个元素。
例如二，假设Kt＝2且按照从大到小的顺序，即一共要根据Bayer矩阵从第t个图像块中选择Kt＝2个元素，假设元素值从大到小依次为4、3和0(依次分别对应有一个元素、两个元素、一个元素)，那么最终选择的Kt＝2个元素包括一个元素值为4的元素和一个元素值为3的元素。其中，Kt＝2中第一个元素为元素值为4的元素；而第Kt＝2个元素的元素值为3，该元 素值3对应有两个元素，那么从元素值为3的元素中任意选择一个作为第Kt＝2个元素。至此，本例已经根据Bayer矩阵从第t个图像块中选择出Kt＝2个元素。
从以上两个例子可以看出，上述方法是按照元素值的顺序从第t个图像块挑选元素的，对于同一个元素值可能对应有两个及其以上的元素，可以任意选择一个即可。
本发明实施例中，所述将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的剩余的Z位所表示的像素值赋值给矩阵Pt(i,j)，包括：
将第t个图像块的高Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的低Z位所表示的像素值赋值给矩阵Pt(i,j)。
下面解释一下本实施例一种涉及的几个个概念，色深、颜色空间和颜色分量。
这里，色深(Color Depth)亦可称为色位深度，是用位(bit)数来表示终端色彩数目的单位，其中，bit是计算机计算的二进制单位(或位)。色深采用2的幂指数来表示，bit数愈高，色深值便愈高，图像所能表现的色彩也愈多。
1bit的图像即2的1次方，只能表现黑与白两种颜色。2bit的图像，则是2的平方可以表现4种颜色，所以除了黑白之外，还可以表现它们之间的两种灰调。而3bit的图像，就是2的3次方(＝8)，表示在一幅黑白或灰阶的照片中，可以表现出包括黑白在内的8种色彩。根据以上计算方法，24bit的图像即可显示16,777,216种色彩，十分接近肉眼所能分辨的颜色，所以被称为真色彩(True color)。而且，24bit色深已成为现时彩色扫描仪的最基本要求，最高的更已达至36bit或48bit。
图像在终端设备上采用颜色空间(也称彩色模型、又称彩色空间或彩 色系统)来表示，目前比较主流的颜色空间主要包括RGB颜色空间、CMY颜色空间、HSV颜色空间和Lab颜色空间，其中：RGB颜色空间是依据人眼识别的颜色定义出的空间，可以表示大部分颜色，其中R(Red)表示红色，G(Green)表示绿色、B(Blue)表示蓝色。CMY是工业印刷采用的颜色空间，它与RGB颜色空间相对应，其中C(Cyan)表示青色，M(Magenta)表示洋红色、Y(Yellow)表示黄色。HSV颜色空间是根据颜色的直观特性由A.R.Smith在1978年创建的一种颜色空间，也称六角锥体模型(Hexcone Model)。其中，H(Hue)表示色调、S(Saturation)表示饱和度、V(Value)表示亮度。L*a*b颜色空间用于计算机色调调整和彩色校正，它独立于设备的彩色模型实现。
下面来说明一下颜色分量的含义，以RGB颜色空间为例，当图像采用RGB颜色空间表示后，那么图像就采用三个维度R、G、B来表示，其中每一个维度R、G、B就是一个颜色分量，前面虽然是以RGB颜色空间为例，但是关于颜色分量的含义同样适用于其它的颜色空间如CMY颜色空间。
本发明实施例中，根据待处理图像的色深X位与显示设备的色深Y位之差Z位确定Bayer矩阵；按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的剩余的Z位所表示的像素值赋值给矩阵Pt(i,j)；将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中Kt为整数；利用所述Kt对Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值；如此，能够在消除光带现象的同时，保持原始图像的显示效果。
实施例二
本发明实施例提供一种图像处理方法，应用于终端，该图像处理方法所实现的功能可以通过终端中的处理器调用程序代码来实现，当然程序代 码可以保存在计算机存储介质中，可见，该终端至少包括处理器和存储介质。
图6为本发明实施例二图像处理方法的实现流程示意图，如图6所示，该方法可以包括：
步骤601，计算视频源的色深和终端上显示设备的色深之差，根据色深之差选择Bayer矩阵。
这里，举例来说，把R、G和B三个色彩分量的色深(位宽)都是8bit，如果要将8bit的视频源(待处理图像)显示在R、G和B分别是5bit、6bit和5bit的显示器上，则R色彩分量分别需要做3的抖动，即需要选择与3bit对应的Bayer矩阵；G色彩分量分别需要做2bit的抖动，即需要选择与2bit对应的Bayer矩阵；B色彩分量分别需要做3bit的抖动，即需要选择与3bit对应的Bayer矩阵。
假设对于某个颜色分量(又称为色彩分量)，视频源的色深是X bit，终端的显示设备的色深是Y bit，当Y<X时，令Z＝X-Y，Z就是视频源在终端的显示设备上显示将要减少的位数(简称截位)。抖动算法就是要对每个像素要减少的Z bit做处理，补偿在截位后的图像上，一般把这种处理称为Z bit的抖动。对于Z bit的抖动，需要选择与Z bit对应的Bayer矩阵。Z可以是大于0的任意整数，都有相应的Bayer矩阵与之对应，本发明实施例中以Z bit为1bit、2bit、3bit和4bit为例，其中，图1所示的是Z bit为1bit时的Bayer矩阵，图2所示的是Z bit为2bit时的Bayer矩阵，图3所示的是Z bit为3bit时的Bayer矩阵，图4所示的是Z bit为4bit时的Bayer矩阵。
步骤602，将Bayer矩阵中像素截掉的数值之和除以对矩阵中的像素总数，并向下取整得到结果Kt。
这里，步骤602具体的操作是：
步骤6021，按照步骤S201中选择的Bayer矩阵把图像划分成Q个图 像块；
这里，Q个图像块中的每一图像块中的像素点都与Bayer矩阵中元素一一对应，假设Bayer矩阵为N×N的矩阵，那么图像块中也包括N×N个像素。
步骤6022，针对于第t个图像块，把第t个图像块中像素的低Z bit所对应的数值(像素值)加起来，得到St，其中t为大于等于1小于等于Q的整数。
这里，假设这个Bayer矩阵块是N×N大小的矩阵块，对于第t个图像块，St可以采用公式(2)来计算：
Figure PCTCN2015096808-appb-000007
公式(2)中，i表示水平方向维度，j表示垂直方向的维度；对于第t个图像块，与Bayer矩阵块相对应的像素(i，j)的总像素值(X bit)是At(i,j)，像素(i，j)的高Y bit的像素值为Bt(i,j)，像素(i，j)的低Z bit的像素值Pt(i,j)，其中，高Y bit的像素值为Bt(i,j)实际上就是待处理图像被截位后的像素值(以下简称截位后的像素值)，截位后的像素值Bt(i,j)与总像素值At(i,j)之间的关系可以用公式(3)来表示：
Bt(i,j)＝At(i,j)/(2z)  (3)。
公式(3)中，总像素值At(i,j)除以2的Z次幂即为截位后的像素值Bt(i,j)，Z表示色深之差。
步骤6023，针对于第t个图像块，将St除以Bayer矩阵中的像素总数L，并向下取整得到Kt。
这里，对于第t个图像块，那么Kt可以采用公式(4)来计算：
Figure PCTCN2015096808-appb-000008
公式(4)中，/表示除法运算，
Figure PCTCN2015096808-appb-000009
表示向下取整。
下面举例来说明上面的步骤S2022至S2023，比如与3bit的抖动对应 的Bayer矩阵是4×4的(参见图3)，即N为4，从左到右从上到下把待处理的图像划分成4×4的图像块，如图7所示，假设4×4矩阵中第1行的像素的低3bit的数值Pt(1,j)依次是1、3、5、7，1≤j≤4；4×4矩阵中第2行的像素的低3bit的数值Pt(2,j)依次是6、5、4、3，1≤j≤4；4×4矩阵中第3行的像素的低3bit的数值Pt(3,j)依次是0、2、4、6，1≤j≤4；4×4矩阵中第4行的像素的低3bit的数值Pt(4,j)依次是2、3、4和5，1≤j≤4；那么St＝1+3+5+7+6+5+4+3+0+2+4+6+2+3+4+5＝60。当St为60时，
Figure PCTCN2015096808-appb-000010
这里，待处理图像即输入到本发明实施例中的图像，换句话说，可以理解为视频源的图像；在采用Bayer矩阵对待处理图像进行划分的过程中，有可能存在不能正好划分的情况，需要说明的是，本发明实施例提供的技术方案同样适用于不能正好划分的情况。例如，上例中不够4×4的块也是把低3位的像素值加起来，除以该图像块内的像素总数，即得到该图像块的Kt。
步骤603，按照Bayer矩阵中元素值从小到大或从大到小的顺序，从Bayer矩阵选择Kt个元素；将与Kt个元素对应的截位后的像素值加1，见公式(5)：
Rt(i,j)＝Bt(i,j)+1  (5)；
公式(5)中Rt(i,j)为对截位后的像素值Bt(i,j)进行修正后的像素值，其中，Bt(i,j)＝At(i,j)/(2z)；
这里，举例进行说明，对于3bit的抖动(参见图3)，S202步骤中得到的Kt是3，这里以Bayer矩阵中元素值从小到大的顺序为例来说明从在Bayer矩阵中选择元素，这样Bayer矩阵选择出的元素一共包括三个，其中包括两个元素值为0的元素和一个元素值为1的元素，然后给Bayer矩阵中元素值是0的两个元素对应的像素值加1，再在Bayer矩阵中元素值是1的 两个元素对应的两个像素值中任选一个，加1。
这里需要说明的是，如果Bayer矩阵中的元素值没有重复的，直接找就行。比如2bit的抖动(参见图2)，如果Kt是3，就给Bayer矩阵中0，1和2三个元素对应的像素值加1就行；其它抖动矩阵以此类推。对于不能将图像进行正好划分的情况，不够Bayer矩阵大小的图像块的处理方式与上面一样，与Bayer矩阵对应的时候，可以采用的方法是图像块的左上角像素与Bayer矩阵的左上角重合，其它像素按照从上到下、从左到右的顺序对应。
比如，采用3bit抖动矩阵处理一张图像，发现右边剩余个3×4的图像块。用这个图像块的左上角对应图3中矩阵的左上角，用到的是前三列。后面的处理方式和4×4块的一样，这里仍然以从小到大的顺序为例，给矩阵中小的数字对应的像素优先加1；数字相同情况下，任意选一个。
需要说明的是，在步骤603中虽然是以从小到大的顺序为例，但是本领域的技术人员应当理解的是，步骤603中同样可以采用从大到小的顺序，为节约篇幅和看起来简洁，因此不再赘述。
步骤604，判断Rt(i,j)是否溢出，如果Rt(i,j)溢出，像素(i,j)最终的输出值Rt-output(i,j)为输出终端的显示设备能显示的最大值2Y，反之，像素(i,j)最终的输出值Rt-output(i,j)为Rt(i,j)。
这里，像素(i,j)最终的输出值Rt-output(i,j)采用公式(6)计算：
Figure PCTCN2015096808-appb-000011
这里，当Rt(i,j)溢出时，终端的显示设备输出像素点(i,j)的像素值即为终端的显示设备能显示的最大值(2Y)；反之，输出Rt(i,j)。
实施例三
基于前述的方法实施例，本发明实施例提供的图像处理装置中的确定单元、划分单元、赋值单元、处理单元和修正单元，以及修正单元中的各 模块都可以通过终端中的处理器来实现；当然也可通过具体的逻辑电路实现；在具体实施例的过程中，处理器可以为中央处理器(CPU)、微处理器(MPU)、数字信号处理器(DSP)或现场可编程门阵列(FPGA)等。
图8-1为本发明实施例三图像处理装置的组成结构示意图，如图8-1所示，该图像处理装置800包括确定单元801、划分单元802、赋值单元803、处理单元804和修正单元805，其中：
所述确定单元801，配置为根据待处理图像的色深X位与图像处理设备的色深Y位之差Z位确定Bayer矩阵，其中，X为大于Y的整数，Z表示色深之差，所述Bayer矩阵为N×N方阵；
所述划分单元802，配置为按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；
所述赋值单元803，配置为将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的剩余的Z位所表示的像素值赋值给矩阵Pt(i,j)，其中1≤t≤Q，1≤i≤N，1≤j≤N；
所述处理单元804，配置为将预设数值和第t个图像块所对应的矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中Kt为整数，所述Kt用于对Bt(i,j)中像素值进行修正；
所述修正单元805，配置为利用所述Kt对Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值。
本发明实施例中，所述预设数值为所述第t个图像块中像素个数之和；所述处理单元，配置为将第t个图像块所对应的矩阵Pt(i,j)中元素值之和St除以所述第t个图像块中像素个数之和，并向下取整进行处理得到Kt。
本发明实施例中，如图8-2所示，所述修正单元805包括选择模块8051、运算模块8052和输出模块8053，其中：
所述选择模块8051，配置为对于与第t个图像块相对应的Bt(i,j)，按 照Bayer矩阵中元素值从小到大或从大到小的顺序从Bayer矩阵选择Kt个元素；
所述运算模块8052，配置为将所述Bt(i,j)中与所述Kt个元素对应的元素值加1，得到矩阵Rt(i,j)；
所述输出模块8053，配置为判断Rt(i,j)是否溢出，如果Rt(i,j)溢出，所述待处理图像中像素(i,j)最终的输出值Rt-output(i,j)为输出终端的显示设备能显示的最大值2Y；反之，所述待处理图像中像素(i,j)最终的输出值Rt-output(i,j)为Rt(i,j)。
本发明实施例中，所述选择模块，还配置为按照Bayer矩阵中元素值从小到大或从大到小的顺序，当Bayer矩阵中第Kt个元素的元素值对应两个以上的元素时，任选其中之一作为第Kt个元素。
本发明实施例中，所述赋值单元，配置为将第t个图像块的高Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的低Z位所表示的像素值赋值给矩阵Pt(i,j)。
这里需要指出的是：以上装置实施例的描述，与上述方法实施例的描述是类似的，具有同方法实施例相似的有益效果，因此不做赘述。对于本发明装置实施例中未披露的技术细节，请参照本发明方法实施例的描述而理解，为节约篇幅，因此不再赘述。
实施例四
基于前述的方法实施例，如果以软件功能模块的形式实现上述的图像处理方法，并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明实施例的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机、服务器、或者网络设备等)执行本发明各个实施例 所述方法的全部或部分。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read Only Memory)、磁碟或者光盘等各种可以存储程序代码的介质。这样，本发明实施例不限制于任何特定的硬件和软件结合。
相应地，本发明实施例再提供一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，该计算机可执行指令用于执行本发明实施例中图像处理方法。
基于前述的实施例，本发明实施例在提供一种终端，该终端包括处理器和显示设备，其中：
处理器，配置为根据待处理图像的色深X位与显示设备的色深Y位之差Z位确定Bayer矩阵，其中，X为大于Y的整数，Z表示色深之差，所述Bayer矩阵为N×N方阵；按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的剩余的Z位所表示的像素值赋值给矩阵Pt(i,j)，其中1≤t≤Q，1≤i≤N，1≤j≤N；将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中Kt为整数，所述Kt用于对Bt(i,j)中像素值进行修正；利用所述Kt对Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值；
显示设备，配置为显示经过所述处理器处理过的图像，所述显示设备的色深为Y。
应理解，说明书通篇中提到的“一个实施例”或“一实施例”意味着与实施例有关的特定特征、结构或特性包括在本发明的至少一个实施例中。因此，在整个说明书各处出现的“在一个实施例中”或“在一实施例中”未必一定指相同的实施例。此外，这些特定的特征、结构或特性可以任意适合的方式结合在一个或多个实施例中。应理解，在本发明的各种实施例 中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本发明实施例的实施过程构成任何限定。
在本申请所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，如：多个单元或组件可以结合，或可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的各组成部分相互之间的耦合、或直接耦合、或通信连接可以是通过一些接口，设备或单元的间接耦合或通信连接，可以是电性的、机械的或其它形式的。
上述作为分离部件说明的单元可以是、或也可以不是物理上分开的，作为单元显示的部件可以是、或也可以不是物理单元；既可以位于一个地方，也可以分布到多个网络单元上；可以根据实际的需要选择其中的部分或全部单元来实现本实施例方案的目的。
另外，在本发明各实施例中的各功能单元可以全部集成在一个处理单元中，也可以是各单元分别单独作为一个单元，也可以两个或两个以上单元集成在一个单元中；上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：移动存储设备、只读存储器(Read Only Memory，ROM)、磁碟或者光盘等各种可以存储程序代码的介质。
或者，本发明上述集成的单元如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。 基于这样的理解，本发明实施例的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机、服务器、或者网络设备等)执行本发明各个实施例所述方法的全部或部分。而前述的存储介质包括：移动存储设备、ROM、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以所述权利要求的保护范围为准。
工业实用性
本发明实施例中，根据待处理图像的色深X位与显示设备的色深Y位之差Z位确定Bayer矩阵；按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；将第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的剩余的Z位所表示的像素值赋值给矩阵Pt(i,j)；将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中所述运算关系包括取整运算，所述Kt用于对Bt(i,j)中像素值进行修正；利用所述Kt对Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值；如此，能够在消除光带现象的同时，保持原始图像的显示效果。

Claims (12)

  1. 一种图像处理方法，所述方法包括：
    根据待处理图像的色深X位与显示设备的色深Y位之差Z位确定Bayer矩阵，其中，X为大于Y的整数，Z表示色深之差；
    按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；
    将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将Z位所表示的像素值赋值给矩阵Pt(i,j)，其中1≤t≤Q，1≤i≤N，1≤j≤N；
    将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，所述运算关系包括取整运算；
    利用所述Kt对所述矩阵Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值。
  2. 根据权利要求1所述的方法，其中，所述预设数值为所述第t个图像块中像素个数之和；所述将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，包括：
    将第t个图像块所对应的矩阵Pt(i,j)中元素值之和St除以所述第t个图像块中像素个数之和，并向下取整进行处理得到Kt。
  3. 根据权利要求1所述的方法，其中，所述利用所述Kt对Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值，包括：
    对于与第t个图像块相对应的Bt(i,j)，按照Bayer矩阵中元素值从小到大或从大到小的顺序从Bayer矩阵对应的第t个图像块选择Kt个元素；
    将所述Bt(i,j)中与所述Kt个元素对应的元素值加1，得到矩阵Rt(i,j)；
    判断Rt(i,j)是否溢出，如果Rt(i,j)溢出，所述待处理图像中像素(i,j)最终的输出值Rt-output(i,j)为输出终端的显示设备能显示的最大值2Y； 反之，所述待处理图像中像素(i,j)最终的输出值R t-output(i,j)为Rt(i,j)。
  4. 根据权利要求3所述的方法，其中，按照Bayer矩阵中元素值从小到大或从大到小的顺序，当Bayer矩阵中第Kt个元素的元素值对应两个以上的元素时，任选其中之一作为第Kt个元素。
  5. 根据权利要求1至4任一项所述的方法，其中，所述将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的剩余的Z位所表示的像素值赋值给矩阵Pt(i,j)，包括：
    将第t个图像块的高Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的低Z位所表示的像素值赋值给矩阵Pt(i,j)。
  6. 一种图像处理装置，所述装置包括确定单元、划分单元、赋值单元、处理单元和修正单元，其中：
    所述确定单元，配置为根据待处理图像的色深X位与图像处理设备的色深Y位之差Z位确定Bayer矩阵，其中，X为大于Y的整数，Z表示色深之差；
    所述划分单元，配置为按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；
    所述赋值单元，配置为将所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将Z位所表示的像素值赋值给矩阵Pt(i,j)，其中1≤t≤Q，1≤i≤N，1≤j≤N；
    所述处理单元，配置为将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中所述运算关系包括取整运算；
    所述修正单元，配置为利用所述Kt对所述矩阵Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值。
  7. 根据权利要求6所述的装置，其中，所述预设数值为所述第t个 图像块中像素个数之和；所述处理单元，配置为将第t个图像块所对应的矩阵Pt(i,j)中元素值之和St除以所述第t个图像块中像素个数之和，并向下取整进行处理得到Kt。
  8. 根据权利要求6所述的装置，其中，所述修正单元包括选择模块、运算模块和输出模块，其中：
    所述选择模块，配置为对于与第t个图像块相对应的Bt(i,j)，按照Bayer矩阵中元素值从小到大或从大到小的顺序从Bayer矩阵选择Kt个元素；
    所述运算模块，配置为将所述Bt(i,j)中与所述Kt个元素对应的元素值加1，得到矩阵Rt(i,j)；
    所述输出模块，配置为判断Rt(i,j)是否溢出，如果Rt(i,j)溢出，所述待处理图像中像素(i,j)最终的输出值Rt-output(i,j)为输出终端的显示设备能显示的最大值2Y；反之，所述待处理图像中像素(i,j)最终的输出值Rt-output(i,j)为Rt(i,j)。
  9. 根据权利要求8所述的装置，其中，所述选择模块，还配置为按照Bayer矩阵中元素值从小到大或从大到小的顺序，当Bayer矩阵中第Kt个元素的元素值对应两个以上的元素时，任选其中之一作为第Kt个元素。
  10. 根据权利要求6至9任一项所述的装置，其中，所述赋值单元，配置为将第t个图像块的高Y位所表示的像素值赋值给矩阵Bt(i,j)，将第t个图像块的低Z位所表示的像素值赋值给矩阵Pt(i,j)。
  11. 一种终端，其特征在于，所述终端包括处理器和显示设备，其中：
    处理器，配置为根据待处理图像的色深X位与显示设备的色深Y位之差Z位确定Bayer矩阵，其中，X为大于Y的整数，Z表示色深之差；按照所述Bayer矩阵对所述待处理图像进行划分，得到Q个图像块；将 所述Q个图像块中的第t个图像块的Y位所表示的像素值赋值给矩阵Bt(i,j)，将Z位所表示的像素值赋值给矩阵Pt(i,j)，其中1≤t≤Q，1≤i≤N，1≤j≤N；将预设数值和所述矩阵Pt(i,j)中元素值之和St，按照预设的运算关系进行处理得到Kt，其中所述运算关系包括取整运算；利用所述Kt对所述矩阵Bt(i,j)中的元素值进行修正，并将修正后的元素值作为所述待处理图像上对应像素的像素值；
    显示设备，配置为显示经过所述处理器处理过的图像，所述显示设备的色深为Y。
  12. 一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，该计算机可执行指令用于执行权利要求1至5任一项所述的图像处理方法。
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111833788A (zh) * 2019-04-19 2020-10-27 北京小米移动软件有限公司 一种屏幕调光方法、装置、终端和存储介质
CN116310352A (zh) * 2023-01-20 2023-06-23 首都医科大学宣武医院 一种阿尔兹海默病mri图像多分类方法及装置
CN116596816A (zh) * 2023-05-10 2023-08-15 海宁奕斯伟集成电路设计有限公司 图像处理装置及方法

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107454469B (zh) * 2017-07-21 2019-11-22 北京奇艺世纪科技有限公司 一种视频图像处理方法及装置
CN114428869B (zh) * 2021-12-20 2025-03-28 北京镁伽科技有限公司 测试图像的输出显示方法、装置及图像信号发生器
CN117253460A (zh) * 2023-09-11 2023-12-19 江西兴泰科技股份有限公司 提高图像显示均匀度的方法、装置、终端设备及存储介质

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7206001B1 (en) * 2004-06-22 2007-04-17 Apple Computer, Inc. Fractal-dithering technique for image display
CN101217027A (zh) * 2008-01-03 2008-07-09 上海广电集成电路有限公司 一种实现16.7m色的frc处理方法
CN102568436A (zh) * 2010-12-16 2012-07-11 苹果公司 时空颜色亮度抖动技术
US20140140608A1 (en) * 2012-11-20 2014-05-22 Samsung Electronics Co., Ltd. Image processing apparatus and method for color-depth demosaicing
CN104303226A (zh) * 2013-02-20 2015-01-21 展讯通信（上海）有限公司 图像抖动方法和系统

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3620521B2 (ja) * 2001-09-14 2005-02-16 日本電気株式会社 画像処理装置、画像伝送装置、画像受信装置及び画像処理方法
CN1187712C (zh) * 2001-10-29 2005-02-02 矽统科技股份有限公司 数字图像信息的抖动方法及装置
CN100435087C (zh) * 2006-10-25 2008-11-19 威盛电子股份有限公司 影像数据抖动方法和装置
CN103970495A (zh) * 2013-06-24 2014-08-06 福州瑞芯微电子有限公司 基于图形处理器实现像素抖动计算的电子装置及方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7206001B1 (en) * 2004-06-22 2007-04-17 Apple Computer, Inc. Fractal-dithering technique for image display
CN101217027A (zh) * 2008-01-03 2008-07-09 上海广电集成电路有限公司 一种实现16.7m色的frc处理方法
CN102568436A (zh) * 2010-12-16 2012-07-11 苹果公司 时空颜色亮度抖动技术
US20140140608A1 (en) * 2012-11-20 2014-05-22 Samsung Electronics Co., Ltd. Image processing apparatus and method for color-depth demosaicing
CN104303226A (zh) * 2013-02-20 2015-01-21 展讯通信（上海）有限公司 图像抖动方法和系统

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
CHEN, XIANJUN ET AL.: "Research Of Half-toning Dithering Technique Using Hexagon Grids", COMPUTER ENGINEERING AND APPLICATIONS, vol. 35, no. 36, 31 December 2009 (2009-12-31) *
LIU, ZHENGLIN ET AL.: "Image Color Enhancement Technique Based On Improved Bayer Dithering Algorithm", JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY, vol. 34, no. 5, 31 May 2006 (2006-05-31) *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111833788A (zh) * 2019-04-19 2020-10-27 北京小米移动软件有限公司 一种屏幕调光方法、装置、终端和存储介质
CN111833788B (zh) * 2019-04-19 2023-08-04 北京小米移动软件有限公司 一种屏幕调光方法、装置、终端和存储介质
CN116310352A (zh) * 2023-01-20 2023-06-23 首都医科大学宣武医院 一种阿尔兹海默病mri图像多分类方法及装置
CN116310352B (zh) * 2023-01-20 2024-04-12 首都医科大学宣武医院 一种阿尔兹海默病mri图像多分类方法及装置
CN116596816A (zh) * 2023-05-10 2023-08-15 海宁奕斯伟集成电路设计有限公司 图像处理装置及方法

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