WO2011113287A1

WO2011113287A1 - Method and device for reducing dynamic false contour of plasma display screen

Info

Publication number: WO2011113287A1
Application number: PCT/CN2010/080414
Authority: WO
Inventors: 徐世文
Original assignee: 四川虹欧显示器件有限公司
Priority date: 2010-03-17
Filing date: 2010-12-28
Publication date: 2011-09-22
Also published as: CN101777303A; CN101777303B

Abstract

A method and a device for reducing dynamic false contour of a plasma display screen are provided, wherein the method comprises obtaining the pixel point data of each same position in the same region of a current frame and an adjacent last frame (S11), calculating an average false contour evaluation value of pixels in the region based on the pixel point data (S12), and performing optimized coding on pixels at each position in the region of the current frame if the average false contour evaluation value is greater than a threshold value (S13).

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to the field of plasma display technology, and more particularly to a method and apparatus for reducing the dynamic false contour of a plasma display panel. BACKGROUND OF THE INVENTION AC Plasma Display Panel (AC PDP) uses multi-subfield technology to realize multi-gradation display of images, that is, one frame of image is divided into multiple subfields for display, and different subfields have different weights. The subfields with different weights correspond to different brightness weights, that is, the number of sustain discharges is displayed when the circuit is implemented, and the multi-level gray scale display of the image can be realized by combining the subfields of different weights. The image of the AC plasma display is divided into 8 subfields as an example (subfield: SF). The weight relationship of these eight subfields is SF1: SF2: SF3: SF4: SF5: SF6: SF7: SF8 = 1: 2: 4: 8: 16: 32: 64: 128. As shown in Fig. 1, a total of 256 gray levels between 0 and 255 can be obtained by different combinations of the eight subfields. For example, when gradation level 0 is achieved, SF1-SF8 are all turned off (OFF), and no discharge luminescence is generated. When gradation level 127 is required, SF1-SF7 is all lit (ON), and SF8 is off (OFF); When gradation 255 is generated, SF1-SF8 are all lit (ON) „ In the display device that realizes multi-gradation by sub-field technology, image distortion of Dynamic False Contour (DFC) is generated. The cause of the pseudo-contour is caused by the subfield technique on the one hand and the integral effect of the human eye on the other hand. The dynamic pseudo-contour has become an important factor restricting the image quality of the AC PDP image. Assume that there is an image moving from left to right on the screen, and there are only two pixels of gray level 127 and 128 on the image, ^ is shown in Figure 2, 128 is on the left, and 127 is on the right. The display principle of the field, when displaying the gray level 127, SF1~SF7 are turned on (ON), and SF8 is turned off (OFF), that is, the display is displayed in about the first 7/8 part of the display time of each frame; When SF1 to SF7 are turned off (OFF) and SF8 is turned on (ON), that is, only The display time of each frame is about 1/8th of the time. Now assume that the image moves at a speed of 8 pixels per frame. According to the visual characteristics of the human eye, the viewpoint will be 8 consecutive pixels along the moving direction. The light emitted by the points in different time periods is accumulated. According to the above principle, there will be such a situation: that is, at some viewpoints On the integral path, the pixel points to be integrated are all extinguished during the integration period, leaving a black dark area on the retina, which shows a gray level of 0, so we will I felt a dark line that didn't exist. This situation is a dynamic pseudo-contour phenomenon, and since the gradation of the image produced here is smaller than the original gradation, it is also called the dynamic pseudo-contour of the negative polarity. Based on the same analysis, see Figure 3, there are only two adjacent grayscale pixels 127 and 128 on the image, 127 on the left and 128 on the right. If the image moves from right to left and the motion speed is also 8 pixels per frame, a continuous lit pixel state will appear on the integration path of some viewpoints, in this case, at 128 and 127 grayscales. At the junction, the human eye will feel a bright area that does not exist (the gray level is 255). This condition is called a positive pseudo-contour of the positive polarity. However, if the adjacent gray levels are 63 and 127, and move in a similar situation as before, there will be no gray level disorder (ie, gray levels other than 63 and 127 will not be observed). ), this is mainly because the illuminating subfields that make up the two gray levels are continuously arranged, and there is no discontinuity in the middle: when displaying 63, SF1 to SF6 are lit, SF7 to SF8 are off; when 127 is displayed, SF1 is displayed. ~SF7 lights up, SF8 1⁄2i^. According to the above analysis, the unevenness of the subfield luminescence in time distribution is the root cause of the dynamic pseudo-contour. The principle of this kind of principle cannot be completely eliminated. We can only take some appropriate measures. Try to suppress the false contours without damaging the original image quality, making it difficult for the human eye to detect. A number of processing methods have been proposed for suppressing dynamic pseudo contours, such as increasing the number of subfields, dividing the large weight subfield method, adjusting the subfield display order method, the compensation pulse method, and the error diffusion method. However, at present, these methods have a problem of poor suppression effect in suppressing dynamic pseudo contours. SUMMARY OF THE INVENTION The present invention is directed to a method and apparatus for reducing the dynamic false contour of a plasma display panel that is capable of solving the problem of suppressing dynamic false contours. According to an aspect of the present invention, a method for reducing a dynamic pseudo contour of a plasma display panel includes: obtaining pixel point data of a same position in a same frame and a same area in an adjacent previous frame; Calculating an average pseudo contour evaluation value of the pixels in the area by using the pixel point data; if the average false contour evaluation value is greater than the threshold value, optimizing encoding of each position pixel in the area of the current frame. Preferably, the process of calculating the average pseudo-contour evaluation value of the pixels in the area includes: acquiring coding statistical values of the pixels in the same position in the current frame and the adjacent previous frame; acquiring the pixel points in the respective positions at the current a frame, a gray level difference value in an adjacent previous frame; a pseudo contour is calculated by the encoding statistical value of each pixel point, the gray level difference value, and a gray level value of the pixel in the current frame The evaluation value is calculated by the obtained pseudo contour evaluation value of each pixel at the same position to calculate the average false contour evaluation value in the region. Preferably, the process of obtaining the coding statistics of the pixels of the same location in the current frame and the adjacent previous frame includes: dividing each frame of pixel data into subfields, and placing each location pixel in the current frame and adjacent The coded exclusive OR value in each subfield of the previous frame is multiplied by the subfield weight value, and the product values in the respective subfields are summed as the coded statistical value of the position pixel; until all the pixels in the same position are acquired The coding statistics of the points; the coding statistics are calculated by the following formula

For the subfield number, n is the frame number, and SP(P) is the weight value of the Pth subfield.

B The coded exclusive OR value of the p-th subfield in the nth frame and the n-1th frame. Preferably, the process of calculating the pseudo contour evaluation value comprises: obtaining a difference between the coding statistical value and the gray level difference value, and using the difference value and a gray level of the pixel point in the current frame The product of the gradation values is used as a pseudo-contour evaluation value; wherein, the difference of the gradation levels is calculated by the following formula:

Where I is the gradation value of the pixel at the position in the nth frame or the η-1 frame, and (X, y) is the pixel coordinate position. Preferably, the process of optimizing encoding comprises: selecting a gray level of each pixel in the area according to a reference encoding table to select a coded output. Preferably, the process of selecting the coded output according to the reference code table comprises: finding a coded output corresponding to the same gray level in the gray level matching reference code table of the pixel; if the gray level of the pixel is in the reference code table If there is no same gray level, the coded output corresponding to the gray level closest to the gray level of the pixel is selected in the reference code table, and the gray level of the pixel is closest to the reference code table. The difference in gray level is subjected to error diffusion processing. According to another aspect of the present invention, an apparatus for reducing a dynamic pseudo contour of a plasma display panel is provided, comprising: a reading unit, configured to obtain pixel point data of each same position in a same frame and an adjacent previous frame An operation unit, configured to calculate, by using the pixel data obtained by the reading unit, an average pseudo-contour evaluation value of the pixel in the area; and an optimization unit, configured to determine that the average pseudo-contour evaluation value is greater than a threshold, Each position pixel within the region of the frame is optimally encoded. Preferably, the operation unit includes: an encoding statistic value module, configured to acquire coding statistic values of respective pixels at the same position in a current frame and an adjacent previous frame; a gradation operation module, configured to acquire pixel points at each position a current frame, a gray level difference value in an adjacent previous frame; an evaluation value operation module, configured to pass the coding statistical value of each pixel point, the gray level difference value, and a pixel point in a current frame The gray level value calculates a pseudo contour evaluation value; The averaging module is configured to calculate an average pseudo contour evaluation value in the region by using the obtained pseudo contour evaluation values of the pixels at the same position. Preferably, the coding statistic module includes: a segmentation sub-module, configured to divide each frame of pixel data into sub-fields; and an operation sub-module, configured to position each location pixel in a current frame and an adjacent previous frame. The coded exclusive OR value in each subfield is multiplied by the subfield weight value, and the product values in each subfield are summed as the coding statistics of the position pixel; the storage submodule is used to store all the acquired identical An encoding value of the position pixel; the evaluation value operation module includes: a difference sub-module, configured to obtain a difference between the coded statistical value and the gray level difference, and a product value sub-module, The product of the difference value and the gray level value of the pixel in the current frame is used as the pseudo contour evaluation value. Preferably, the optimization unit includes a discriminating module, an encoding module, and an error diffusion module: the discriminating module is configured to trigger the encoding module when the average pseudo contour evaluation value is greater than a threshold; Searching for the coded output corresponding to the same gray level in the gray level matching reference code table of the pixel; or when the gray level of the pixel does not have the same gray level in the reference code table, The coding output corresponding to the gray level closest to the gray level of the pixel is selected in the coding table, and the error diffusion module is triggered; the invention uses the average false contour evaluation value as a judgment basis, thereby effectively preventing the false contour phenomenon In addition, the average pseudo-contour evaluation value combines the pixels of the same position in the front and back frames, and the weighting value, and the accuracy of the judgment is high, and the calculation process is simple and efficient. BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are set to illustrate,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, In the drawing: FIG. 1 is a schematic diagram showing the weight ratio of each subfield when the image is divided into 8 subfields; FIG. 2 is a view showing the distribution of the discharge luminescence of the pixel unit in time and space when the negative dynamic pseudo-contour is displayed; FIG. 3 shows FIG. 4 shows a flow chart of a first embodiment of the present invention; FIG. 5 shows a schematic diagram of a mode for generating a dynamic false contour; FIG. FIG. 7 is a schematic diagram showing the error diffusion; FIG. 8 is a schematic flowchart of the third embodiment of the present invention; FIG. 9 is a schematic structural view of the apparatus according to the fourth embodiment of the present invention; . DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS In order to clearly illustrate the method and apparatus of the present invention, the present invention will be described in detail below with reference to the accompanying drawings. Referring to FIG. 4, FIG. 4 is a flowchart of Embodiment 1 of the present invention, including:

S11: obtaining pixel data of each same position in the same area in the current frame and adjacent one frame;

S12: calculating an average pseudo contour evaluation value of the pixels in the area by using the pixel data;

S13: If the average pseudo-contour evaluation value is greater than the threshold value, optimal coding and error diffusion are performed on each position pixel in the region of the current frame. Since the gradation levels of two consecutive frames are similar, and the distribution pattern of the subfield coding is different, the false contour produces a higher rate of 4. As shown in FIG. 5, it describes the case of a code distribution pattern when a pseudo contour is generated. Under the weight of the subfield [1, 2, 4, 8, 16, 32, 64, 128], the encoding of the grayscale 127 is 11111110, the encoding of the grayscale 128 is 00000001, and if the grayscale 127 of the edge image of a certain frame is displayed, The gray image of the edge image displayed in the lower frame of the image is 128, then the dynamic pseudo contour occurs when the 127 transitions to 128. According to the ideal state, the human eye first perceives 127 grayscale, and then perceives 128 grayscale. But the actual situation is not the case, see subfield separation display technology The principle, in the continuous display of 127 to 128, the lighting coding sequence: 1111111000000001, during the conversion of different gray scale display, the human eye has integrated the image eight times. A gray level is perceived every time it is integrated. If the perceived gray level in the eight points is greatly deviated from the displayed gray level, the human eye feels a dynamic false contour. For example, the grayscale display changes from 127 to 128. The columns from the first subfield to the eighth subfield in the order shown are 11111110 and 00000001, respectively. The above figures are sequentially divided into 127, 63, 31, 15 , 7, 3, 1, 0, 128. When the product is divided into 0, the human eye feels a clear dark streak. The invention discriminates according to the average pseudo contour evaluation value of the pixels in the same area of the two frames before and after, and the pseudo contour recognition rate is high, because the dynamic image is a frame and frame image superposition effect, so the pixels at the same position between the frames before and after the detection are detected. Pseudo contour phenomenon. Optimized coding and error diffusion processing for pixels prone to false contours can effectively reduce the false contour of the image and eliminate the false contour of the human eye. When the pixels are evaluated, there are various forms of pseudo contour evaluation values, such as the values of the MPD algorithm operations. The pseudo contour evaluation values used in the present invention are described below by the second embodiment of the present invention. See Figure 6, including:

S21: Obtain pixel data of the same position in the same area of the current frame and the adjacent previous frame; the obtained pixel data includes: a pixel code value of the current frame, adjacent to the previous frame, at each same position in the area The coded value, the weight of the subfield to which the coordinates of this position belong, and the gray level of the subfield to which the position belongs in the current frame, and the gray level in the adjacent previous frame.

S22: Obtain coding statistical values of pixels in the same position in the current frame and adjacent previous frames; first, divide one frame of pixel data into subfields, and the plasma display controller receives externally input RGB image signals and control signals , divides an image into several subfields, each of which includes reset time, addressing time, and hold time. Obtaining the coded XOR value of each position pixel in each subfield of two frames (the current frame, the adjacent previous frame) is multiplied by the subfield weight value, and then summing the product values in each subfield as The coded statistical value A of the position pixel is obtained until the coding statistics of all the pixels at the same position are obtained. The formula is as follows:

Where P and m are subfield numbers, n is a frame number, and SP(P) is a weight value of the Pth subfield, such as 1, 2, 4, 8, 16, 32, 64 or 128, where B is the pixel The encoding corresponding to the gray level, "„VW,"„-i V ^ Whether the front and rear frames are lit or off in p subfields, the code value is 0 or 1 value. Here, Bn refers to an encoded value of each pixel in P subfields such as 10101001.

S23: Obtain a gray level difference value of each position pixel in the current frame and the adjacent previous frame;

Where I is the gradation value of the position pixel in the nth frame, and (X, y) is the pixel coordinate position.

S24: Calculate a pseudo contour evaluation value by using the encoding statistical value, the gray level difference value, and a gray level value of the pixel in the current frame; acquiring between the encoding statistical value and the gray level difference value The difference between the difference and the gray level value of the pixel in the current frame as the pseudo contour evaluation value C, the pseudo contour evaluation value

C = (A - B)I _n (x, y) _;

S25: Calculate the average pseudo-contour evaluation value in the area by using the acquired pseudo-contour evaluation values; sum the obtained pseudo-contour evaluation values in the area and perform an averaging operation to obtain an average pseudo contour in the area Evaluation value.

S26: determining whether the pseudo-contour evaluation value is greater than a threshold value, if not, that is, less than the threshold value, indicating that no false contour phenomenon occurs in the area, and executing S27; if yes, that is, greater than the threshold value, executing S28;

S27: directly outputting the code corresponding to the gray level of each pixel;

S28: Selecting a gradation level of each pixel in the region according to a reference coding table; the reference code table is a selected code corresponding to the gradation level, and the code corresponding to each gradation level in the reference code table There is no false contouring between them. In the selection process, if the gray level of the pixel does not have the same gray level in the picking code table (ie, the reference code table), then the code in the selected code table is displayed with the nearest gray level, so that they will There is a difference, and the difference is subjected to error diffusion processing to the adjacent point. The error diffusion is to diffuse the variation error of the pixel color when the color depth is lowered. This causes the naked eye to observe the picture, and the error of the entire set of adjacent pixel points becomes small. The following is an example to illustrate that it is easy to understand. For example: There is one pixel on the original 256-level grayscale image, and the grayscale is 120 (0~255). If you want to convert the pixel to ₁₆ grayscale, the easiest way is to divide the pixel by 16, Then the converted value is 120/16=7.5, which is 7 after the integer number is reserved. This converted value has an error of 0.5. The simplest method of error diffusion is to put the error of 0.5 on the right, bottom right, and bottom points of this point. As shown in Figure 7, it can be assigned to the right, lower right, in a ratio of 3:2:3. At the lower point, add (0.5* 16)*3/8=3 to the gray level of the right and bottom points, and add (0.5*16)*2/8=2 to the lower right point. The whole graph is much better than the direct removal of the error. The reference code table can be in the form of optimized coding according to a certain principle. This kind of coding form transition can suppress the processing of pseudo contours, then the gray level transition between pixels of the same point can suppress the false contour, and the different pixel positions are similar in coding form, then the integration effect of the human eye on different pixel positions will not be obvious. Pseudo-contour. However, the disadvantage of the entire field of uniform coding is the absence of gray levels. To compensate for this, the error diffusion of the gradation can be performed. The range of regions in which pixels are selected in the two frames of the present invention may be selected according to the case of the data stream, or the pixels in the entire frame may be used as the object of evaluation. The invention adopts the average pseudo-contour evaluation value as the judgment basis, and can effectively prevent the occurrence of the pseudo-contour phenomenon; in addition, the average pseudo-contour evaluation value integrates the pixels of the same position of the front and rear frames, and the weighting value, and the accuracy of the judgment is high, and the operation is high. The process is simple and efficient. The method flow of the present invention is described in detail above. The method flow of the present invention can be implemented by a plurality of structural devices. The preferred embodiment is described below to illustrate the device of the present invention. Referring to the structural diagram of the third embodiment in FIG. 8, the method includes: a frame memory 82 for storing one frame of pixel point data, a unit 81 for performing false contour detection on the current frame pixel point data and the previous frame pixel point data, and a unit 83 for performing gray scale adjustment on the current frame pixel point data, for the pixel point The data is subjected to a unit 84 of error diffusion processing. Embodiment 4 of the present invention further provides a device, and the structure of the device is as shown in FIG. 9, and includes: The reading unit 91 is configured to read the pixel data of the same position in the same area and the same area in the adjacent previous frame; the operation unit 92 is configured to calculate the area by using the pixel data obtained by the reading unit The average pseudo-contour evaluation value of the inner pixel; the optimizing unit 93 is configured to perform optimal encoding on each position pixel in the area of the current frame when the average pseudo-contour evaluation value is greater than the threshold value. Preferably, the operation unit 92 in the device includes: an encoding statistic module 921, configured to acquire coding statistic values of pixels of the same location in the current frame and adjacent previous frames; a gradation operation module 922, configured to Obtaining a gray level difference value of each position pixel in a current frame and an adjacent previous frame; an evaluation value operation module 923, configured to pass the coding statistical value, the gray level difference value, and each pixel point The gradation value of the pixel in the current frame is calculated as a pseudo-contour evaluation value; the averaging module 924 is configured to calculate an average pseudo-contour evaluation value in the region by using the obtained pseudo-contour evaluation value of each pixel at the same position. Preferably, the coding statistic module 921 in the apparatus includes: a segmentation sub-module 9211 for dividing each frame of pixel data into respective subfields; and an operation sub-module 9212 for locating each location pixel in the current frame, The coded exclusive OR value in each subfield of the adjacent previous frame is multiplied by the subfield weight value, and the product value in each subfield is summed as the coding statistical value of the position pixel; the storage submodule 9213 is used. And storing the acquired coding statistics of all the same location pixel points; the evaluation value operation module 923 includes: a difference value module 9231, configured to obtain a difference between the coded statistical value and the gray level difference value value, The product value sub-module 9232 is configured to use the product of the difference value and the gray level value of the pixel in the current frame as the pseudo contour evaluation value. Preferably, the optimization unit 93 in the device includes: a discriminating module 931, an encoding module 932, and an error diffusion module 933. The discriminating module 931 is configured to: when the average pseudo contour evaluation value is greater than a threshold, trigger the The encoding module 932 is configured to search for a coded output corresponding to the same gray level in the gray level matching reference code table of the pixel; or when the gray level of the pixel is in the reference code table When there is no same gray level, the coded output corresponding to the gray level closest to the gray level of the pixel point is selected in the reference code table, and the error diffusion module 933 is triggered; the error diffusion module 933 And used to perform error diffusion processing on the difference between the gray level of the pixel and the nearest gray level in the reference code table. The solution in the foregoing method embodiments of the present invention can be implemented by the device embodiment of the present invention, and is described herein. The invention adopts the average pseudo-contour evaluation value as the judgment basis, and optimizes the encoding and diffusion processing of the data, thereby effectively preventing the occurrence of the false contour phenomenon; in addition, the average pseudo-contour evaluation value integrates the pixels of the same position of the front and rear frames, and The weighting value, the accuracy of the judgment is high, and the calculation process is simple and efficient. In addition, the visual characteristics of the human eye are also considered, that is, the human vision is more sensitive to changes in the brightness of the dark field. That is to say, in the case where the pseudo contour is the same, the dark pseudo contour of the picture is more difficult to adapt to the human eye than the false contour of the picture. Therefore, weighting needs to be considered, which means that the weighting of each gray level is determined based on the current gray level. Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general-purpose computing device, which can be concentrated on a single computing device or distributed over a network composed of multiple computing devices. Alternatively, they may be implemented by program code executable by the computing device, such that they may be stored in the storage device by the computing device, or they may be separately fabricated into individual integrated circuit modules, or they may be Multiple modules or steps are made into a single integrated circuit module. Thus, the invention is not limited to any specific combination of hardware and software. The above is only the preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes can be made to the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the scope of the present invention are intended to be included within the scope of the present invention.

Claims

A method for reducing a dynamic pseudo contour of a plasma display panel, comprising: obtaining pixel data of a same position in a same frame and a same area in an adjacent previous frame;

Calculating an average pseudo contour evaluation value of the pixels in the area by using the pixel point data at the same position;

If the average pseudo contour evaluation value is greater than the threshold value, the pixel points of the respective positions in the region of the current frame are optimally encoded.

The method according to claim 1, wherein the calculating the average pseudo contour evaluation value of the pixels in the area comprises:

Obtaining coding statistics values of the pixels in the same position in the current frame and the adjacent previous frame; obtaining the gray level difference values of the pixels in the same position in the current frame and the adjacent previous frame;

Calculating a pseudo-contour evaluation value of the pixel by the coding statistic value of each pixel, the gradation difference value, and the gradation value of the pixel in the current frame;

The average pseudo contour evaluation value in the region is calculated by the obtained pseudo contour evaluation values of the pixels at the same position.

The method according to claim 2, wherein the coding statistics of the pixels in the same position in the current frame and the adjacent previous frame are obtained by the following formula:

Where P is the subfield number, m is the number of subfields divided by the current frame and the adjacent previous frame, n is the frame number, and SP(P) is the weight value of the pth subfield, l O)- ^0)1 is the coded exclusive OR value of the p-th subfield of pixel B in the current frame n and the adjacent previous frame n-1.

4. The method according to claim 2, wherein the process of calculating the pseudo contour evaluation value comprises: Obtaining a difference between the coding statistic value and the gradation difference value, and using a product of the difference value and a gradation value of the pixel point in the current frame as a pseudo contour evaluation value;

Wherein, the gray level difference value is calculated by the following formula:

Where I is the gradation value of the pixel at the position in the nth frame or the n-1th frame, and (X, y) is the pixel coordinate position. The method according to claim 1, wherein the process of optimizing encoding comprises: selecting an encoding of the target in a reference encoding table according to a gray level of each pixel in the region and outputting. The method according to claim 5, wherein the selecting the corresponding encoding in the reference encoding table comprises:

Determining whether there is a gray level corresponding to the gray level of the pixel in the reference code table,

If yes, find the corresponding code according to the gray level of the pixel and output it; if not, select the coded output corresponding to the gray level closest to the gray level of the pixel in the reference code table, The difference between the gray level of the pixel and the nearest gray level in the reference code table is subjected to error diffusion processing. An apparatus for reducing a dynamic pseudo contour of a plasma display panel, comprising: a reading unit, configured to obtain pixel point data of each same position in a same area and an adjacent area in a previous frame;

An operation unit, configured to calculate, by using the pixel data obtained by the reading unit, an average pseudo contour evaluation value of the pixels in the area;

And an optimization unit, configured to perform optimal coding on each position pixel in the region of the current frame when the average pseudo-contour evaluation value is greater than a threshold. The apparatus according to claim 7, wherein the arithmetic unit comprises:

a coding statistics module, configured to obtain coding statistics values of pixels in the same location in the current frame and adjacent previous frames;

a grayscale operation module, configured to obtain a grayscale difference value of each position pixel in a current frame and an adjacent previous frame; An evaluation value calculation module, configured to calculate a pseudo contour evaluation value by using the coding statistical value of each pixel, the gray level difference value, and a gray level value of the pixel in the current frame;

The averaging module is configured to calculate an average pseudo contour evaluation value in the region by using the obtained pseudo contour evaluation value of each pixel at the same position.

9. The apparatus according to claim 8, wherein the coding statistics module comprises:

a dividing sub-module, configured to divide each frame of pixel data into respective subfields; and an operation submodule, configured to encode an exclusive OR value of each position pixel in each subfield of the current frame and the adjacent previous frame The subfield weight values are multiplied, and the product values in the respective subfields are summed as the coding statistics of the position pixels;

a storage submodule, configured to store the encoded code values of all the pixels at the same location acquired;

The evaluation value operation module includes:

a difference submodule, configured to obtain a difference between the coded statistical value and the gray level difference,

The product value sub-module is configured to use the product of the difference value and the gray level value of the pixel in the current frame as the pseudo contour evaluation value.

10. The apparatus according to claim 7, wherein the optimization unit comprises a discriminating module, an encoding module, and an error diffusion module:

The determining module is configured to trigger the encoding module when the average pseudo contour evaluation value is greater than a threshold;

The encoding module is configured to search for a coded output corresponding to the same gray level in the gray level matching reference code table of the pixel; or when the gray level of the pixel does not have the same gray level in the reference code table At the level, the coded output corresponding to the gray level closest to the gray level of the pixel is selected in the reference code table, and the error diffusion module is triggered;

The error diffusion module is configured to perform error diffusion processing on the difference between the gray level of the pixel and the nearest gray level in the reference encoding table.