CN106651807B - Image processing system, display device and image processing method - Google Patents
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Abstract
The invention provides an image processing system, a display device and an image processing method. The image processing system includes: a base image synthesizing unit configured to synthesize a plurality of base images by performing a graying process on a plurality of images having a base shape; the edge smoothing processing unit is used for carrying out edge smoothing processing on the basic image; an edge smoothing coefficient generating unit for extracting the edge smoothing coefficient generated by the edge smoothing processing unit; an edge smoothing coefficient storage unit for storing an edge smoothing coefficient; and an input image computing unit for processing the input image and outputting an output image with smoothed edges. According to the method, the edge smoothing processing is carried out on the basic image in advance to obtain a specific edge smoothing coefficient, and the specific edge smoothing coefficient is stored; when the input image is processed, the proper edge smoothing coefficient can be quickly selected, the image processing speed is increased, and the edge smoothing processing efficiency is improved.
Description
Technical Field
The present invention relates to the field of display, and in particular, to an image processing system, a display device, and an image processing method.
Background
The increasing sophistication of display technology has led to an increasing demand for image display effects. Usually, image display is realized by pixels arranged in an array. However, for a circular display, at its edge, it may appear jagged due to the matrix-like arrangement of pixels. When a picture is displayed, a relatively obvious sawtooth shape appears at the edge of the picture, and the display effect is seriously influenced. In order to improve the image display effect, more and more attention is paid to the smoothing process of the jagged edge.
A common processing method is to divide the edge portion of the image into blocks of a specific size, and then perform edge smoothing processing on each block. In the prior art, a filtering process is usually used to achieve the purpose of smoothing the edges. The filtering effect is related to the selected smoothing coefficient, and the image filtering effect can be best by selecting the proper smoothing coefficient. However, performing the same filtering process on images having the same shape causes unnecessary operation waste and also increases the load on the driving chip of the display screen.
Disclosure of Invention
In view of the above, the present invention provides an image processing system, a display apparatus, and an image processing method for eliminating or reducing the above-mentioned problems in the prior art.
To achieve the above object, the present invention provides an image processing system for performing image processing on an input image having a plurality of pixels arranged in a matrix, comprising: a base image synthesizing unit configured to synthesize a plurality of base images by performing a graying process on a plurality of images having a base shape; an edge smoothing unit, configured to perform edge smoothing on the base image; an edge smoothing coefficient generating unit configured to extract the edge smoothing coefficient generated by the edge smoothing processing unit; an edge smoothing coefficient storage unit for storing the edge smoothing coefficient; and an input image computing unit configured to process the input image and output an edge-smoothed output image.
Further, the base image synthesizing unit processes the base image into a white image including 255 gradations; and/or the base image synthesizing unit processes the base image into a black image including a 0 gray scale.
Further, the edge smoothing unit includes a filtering unit, and the filtering unit performs smoothing filtering on the base image to filter out a portion of the base image where the frequency is located in a preset frequency band.
Furthermore, the filtering mode of the filtering unit is one or a combination of several of gaussian filtering, mean filtering, median filtering and adaptive filtering.
Further, the edge smoothing coefficient generating unit is configured to perform normalization or compression processing on the smoothed base graph, and extract a corresponding edge smoothing coefficient.
Further, the edge smoothing coefficient storage unit is configured to store an edge smoothing coefficient used in the processing of the edge smoothing processing unit, and the edge smoothing coefficient storage unit stores at least one group of edge smoothing coefficients.
Further, the input image arithmetic unit includes: an input image conversion unit for converting the input image into a grayscale image; the addressing unit is used for extracting at least one group of corresponding edge smoothing coefficients from the edge smoothing coefficient storage unit according to the gray level image; an arithmetic unit for applying the edge smoothing coefficient extracted by the addressing unit to the grayscale image; and the output image conversion unit is used for converting the gray level image subjected to the action of the edge smoothing coefficient into an output image.
Further, the edge shape of the base image includes a circle, an ellipse, or a polygon.
Further, the image processing system further comprises a driving chip, and the edge smoothing coefficient storage unit is located inside or outside the driving chip.
Further, the input image operation unit is located inside the driving chip.
The invention also provides a display device comprising the image processing system.
The present invention also provides an image processing method for performing image processing on an input image having a plurality of pixels arranged in a matrix, comprising: a base image synthesis step of performing a gradation process on a plurality of images having a base shape to synthesize a plurality of base images; an edge smoothing step of performing edge smoothing on the base image; an edge smoothing coefficient generating step of extracting the edge smoothing coefficient generated in the edge smoothing processing step; an edge smoothing coefficient storage step of storing the edge smoothing coefficient; and an input image calculation step of processing the input image and outputting an edge-smoothed output image.
Further, the base image synthesizing step processes the base image into a white image including 255 gradations; and/or, the base image synthesizing step processes the base image into a black image including a 0 gray scale.
Further, the edge smoothing processing step includes a filtering step; and the filtering step is used for carrying out smooth filtering processing on the basic image and filtering out the part of the basic image, the frequency of which is positioned in a preset frequency band.
Furthermore, the filtering mode of the filtering step is one or a combination of several of gaussian filtering, mean filtering, median filtering and adaptive filtering.
Further, the input image operation step includes: an input image conversion step for converting the input image into a grayscale image; an addressing step, which is used for extracting at least one group of corresponding edge smoothing coefficients from the edge smoothing coefficient storage step according to the gray level image; an operation step of applying the edge smoothing coefficient extracted in the addressing step to the grayscale image; and an output image conversion step, which is used for converting the gray level image after the edge smoothing coefficient acts into an output image.
According to the image processing system, the display device and the image processing method, the edge smoothing processing is performed on the basic image in advance, so that the edge smoothing coefficient suitable for the specific basic image is obtained and stored. Therefore, when the input image is processed, the proper edge smoothing coefficient can be rapidly selected, the image processing speed is increased, and the edge smoothing processing efficiency is improved. Meanwhile, the input images with the same basic graph are suitable for the same edge smoothing coefficient, so that repeated operation is avoided, and the load of a driving chip of the display equipment is reduced.
Drawings
FIG. 1 is a schematic diagram of an image processing system according to the present invention;
FIG. 2 is a schematic diagram of an input image computing unit according to the present invention;
FIG. 3 is a schematic diagram of an addressing unit according to the present application
Fig. 4 is a schematic structural diagram of a driving chip provided in the present application;
FIG. 5 is a schematic diagram of a display device according to the present application;
FIG. 6 is a flow chart of an image processing method provided in accordance with the present application;
FIG. 7 is a schematic diagram of an input image operation step according to the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, the present invention is further described with reference to the accompanying drawings and examples.
The present invention provides an image processing system, comprising: the image processing apparatus includes a base image synthesizing unit, an edge smoothing processing unit, an edge smoothing coefficient generating unit, an edge smoothing coefficient storing unit, and an input image computing unit. A base image synthesizing unit configured to synthesize a plurality of base images by performing a graying process on a plurality of images having a base shape; the edge smoothing processing unit is used for carrying out edge smoothing processing on the basic image; the edge smoothing coefficient generating unit is used for extracting the edge smoothing coefficient generated by the edge smoothing processing unit; the edge smoothing coefficient storage unit is used for storing the edge smoothing coefficient; the input image computing unit is used for processing the input image and outputting an output image with smoothed edges.
In general, at the edge of a display image, a jagged edge is caused by a matrix-like arrangement of pixels, and the display effect is seriously affected. Aiming at the problem, the embodiment of the invention stores the edge smoothing coefficient of the basic image, and directly calls the stored smoothing coefficient when the input image is processed, thereby improving the efficiency of image processing.
It should be noted that in the following description, specific details are set forth in order to provide a thorough understanding of the present invention. The invention can be implemented in a number of ways different from those described herein and similar generalizations can be made by those skilled in the art without departing from the spirit of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.
Referring to fig. 1, a schematic diagram of an image processing system according to the present invention is shown. The image processing system 100 includes a base image synthesizing unit 1001, an edge smoothing processing unit 1002, an edge smoothing coefficient generating unit 1003, an edge smoothing coefficient storage unit 1004, and an input image operation unit 1005.
A base image combining unit 1001 performs a gradation process on a series of images having a base shape. The graying process is a process of converting the color image into a grayscale image, and the graying method may be a component method, a maximum value method, an average value method, a weighted average method, or the like. In the present embodiment, a preferable graying method is a component method, that is, luminance of three components (a red component, a green component, and a blue component) in a color image is taken as a grayscale value of a grayscale map. Thus, the generated gray map may be composed of the gray values of any one of the red, green and blue components, or may be composed of a weighted average of the gray values of the three components.
Further, the base shape of the image to be subjected to the gradation processing may have any publicly known shape, and may be, for example, a square, a triangle, a circle, or the like.
Further, after the base image synthesizing unit 1001 performs the gradation processing on the image having the base pattern, the obtained base image includes a white image of 255 gradations and a black image of 0 steps. It will be appreciated by those skilled in the art that the base image resulting from the graying process can include a variety of grayscale values. Therefore, the gray scale value of the base image obtained after the graying process is not limited in this embodiment.
The edge smoothing unit 1002 is configured to filter noise of the base image by using a filtering method or the like, so as to smooth the image. The edge smoothing processing unit 1002 includes a filtering unit. During the transmission of signals and the display of images, various noise contaminations, such as electrical noise, are inevitable. The pollution of various noises causes a great amount of false edges of the finally extracted image, and the display effect is influenced. Therefore, the filtering unit may include a band pass filter for passing a signal having a frequency located at a preset frequency band. Specifically, the band-pass filter is configured to filter out components having frequencies higher than a highest value of a predetermined frequency band and components having frequencies lower than a lowest value of the predetermined frequency band.
Specifically, the filtering manner may include gaussian filtering. Gaussian filtering is a linear filtering, which is a process of weighted averaging of the entire image. The value of each pixel point contained in the basic image after the smoothing processing is obtained by weighting and averaging the value of each pixel point and other pixel values of the neighborhood.
Further, the edge smoothing unit 1002 may include various filtering methods. Specifically, the filtering manner may be any one or a combination of gaussian filtering, mean filtering, median filtering, and adaptive filtering. Therefore, the filtering method included in the edge smoothing unit 1002 is not limited in this embodiment.
In the process of edge smoothing, it is usually necessary to select appropriate filter parameters. In particular, the filter parameter may be a filter scale. The decomposition results for each filter scale represent information of the image in a certain frequency range. The small-scale filter is sensitive to edge signals, and the finely changed edge can be obtained on a smaller scale, but the small-scale filter has the defect of being sensitive to noise; the large-scale filter has good noise filtering effect, can obtain stable image edges, and removes fine details. Therefore, in this embodiment, the image under each filtering scale may be subjected to edge extraction, and then the edge images under different scales are fused, so that not only the anti-noise capability can be improved, but also the image itself can be finely restored.
An edge smoothing coefficient generating unit 1003 configured to process the base image to extract an edge smoothing coefficient. Specifically, the processing procedure may be normalization processing. The normalization process causes the edge smoothing coefficients to become a dimensionless series of values whose absolute values have some relative relationship. After a specific input image is received, a series of values obtained in the process are subjected to inverse normalization processing, so that the stored series of values are suitable for a new input image. Therefore, extracting the edge smoothing coefficient using the normalization process is advantageous in making the edge smoothing coefficient suitable for the input image of each situation.
Further, the edge smoothing coefficient generation unit 1003 may also extract an edge smoothing coefficient by performing compression processing on the base image. The compressed image can relatively completely store the original pixel matrix, and therefore, the compressed image can also be used for extracting the edge smoothing coefficient.
An edge smoothing coefficient storage unit 1004, configured to store the normalized edge smoothing coefficient. In the edge smoothing coefficient storage unit, there may be a plurality of sets of edge smoothing coefficients stored at the same time. Those skilled in the art will appreciate that complex graphics may be decomposed and/or approximated as multiple images with underlying graphics. Therefore, when performing edge smoothing processing on an input graph, storing a plurality of edge smoothing coefficients for a specific base graph in advance is advantageous for improving the efficiency of image processing. For example, the edge smoothing coefficient storage unit 1004 may store the edge smoothing coefficient for a rectangle and the edge smoothing coefficient for a triangle at the same time. When the input image has a hexagonal edge contour (the hexagon can be decomposed into a plurality of triangles or into a plurality of rectangles and a plurality of triangles), the edge smoothing processing can be performed on the input image by utilizing the two sets of edge smoothing coefficients.
An input image calculation unit 1005 for processing the input image and outputting an edge-smoothed output image. Please refer to fig. 2, which illustrates a schematic structural diagram of an input image computing unit according to the present invention. In some alternative embodiments, the input image operation unit 1005 further includes an input image conversion unit 11, an addressing unit 12, an operation unit 13, and an output image conversion unit 14.
An input image conversion unit 11 is used for carrying out gray processing on the input image 10. The graying method may be a component method, a maximum value method, an average value method, a weighted average method, or the like. In this embodiment, the preferred graying method is a component method, and a white image including 255 grayscales and a black image of 0 level are finally obtained. The difference from the embodiment of fig. 1 is that the input image conversion unit 11 performs a graying process on the input image, and the base image synthesis unit 1001 performs a graying process on a series of images having a base shape. Note that, in order to ensure that the edge smoothing coefficients stored in the edge smoothing coefficient storage unit 1004 are applied to the input image, the gradation method used by the base image combining unit 1001 is the same as the gradation method used by the input image conversion unit 11.
The addressing unit 12 is configured to obtain a grayed image according to the input image conversion unit 11, and find a corresponding edge smoothing coefficient in the edge smoothing coefficient storage unit 1004. Specifically, please refer to fig. 3, which shows a schematic structural diagram of an addressing unit provided in the present application. In the present embodiment, the addressing unit 12 may include an identifying unit 121 and an extracting unit 122. When the input image is converted into a gray image by the input image conversion unit 11, the recognition unit 121 first recognizes the input image after the graying process and divides an edge portion of the image into a limited number of patterns having basic shapes. The extraction unit 122 extracts the corresponding edge smoothing coefficient from the edge smoothing coefficient storage unit 1004 according to the divided base pattern.
And an arithmetic unit 13 configured to perform edge smoothing processing on the input image after the graying processing, using the edge smoothing coefficient extracted by the extraction unit 122.
And an image conversion unit 14, configured to convert the gray scale map of the input image after the edge smoothing processing into a color output image 15.
In this embodiment, an image having a basic pattern is subjected to edge smoothing processing in advance, and an edge smoothing coefficient is stored. The input image can directly use the stored edge smoothing coefficient, thereby avoiding repeated operation and reducing the load of a driving chip of the display equipment.
In other alternative embodiments, the edge smoothing coefficient storage unit may be located inside the driving chip. Please refer to fig. 4, which shows a schematic structural diagram of a driving chip provided in the present application. The driving chip 200 includes an edge smoothing coefficient storage unit 1004. Specifically, the edge smoothing coefficient storage unit 1004 may be located inside the memory chip of the driver chip 200.
In this embodiment, the driving chip 200 may further include an input image operation unit 1005, i.e., the input image operation unit 1005 is located inside the driving chip 200.
Further, the driving chip 200 further includes other units 1006. Wherein the other unit may include a plurality of units, and the respective units may be different from each other. For example, the other unit 1006 may be any one or more of a touch driving unit, a touch sensing unit, or a switch control unit.
It will be understood by those skilled in the art that the edge smoothing coefficient storage unit may be located inside the driver chip or outside the driver chip. When the edge smoothing coefficient storage unit is positioned in the driving chip, one or more storage chips can be shared with the storage unit of the display panel, so that the circuit is simplified, and the utilization rate of the driving chip is improved. When the edge smoothing coefficient storage unit is positioned outside the driving chip, the smoothing coefficient storage unit independently uses one or more storage chips, so that the difficulty of reading stored data is reduced, and the accuracy of the image processing system is improved. Therefore, the positional relationship of the edge smoothing coefficient storage unit and the driver chip is not limited in the present embodiment.
The invention further provides a display device, please refer to fig. 5, which shows a schematic structural diagram of a display device provided by the present application. The display device referred to in this embodiment includes, but is not limited to, a smart watch, a mobile phone, a tablet computer, a television, and the like. The display device comprises an image processing system 100, which image processing system 100 may be the image processing system described in any of the embodiments above.
The invention also provides an image processing method for processing an input image with a plurality of pixels arranged in a matrix shape, which comprises a basic image synthesis step, an edge smoothing processing step, an edge smoothing coefficient generation step, an edge smoothing coefficient storage step and an input image operation step. Wherein the base image synthesizing step is configured to synthesize a plurality of base images by performing a graying process on a plurality of images having the base shape. The edge smoothing processing step is used for carrying out edge smoothing processing on the basic image. The edge smoothing coefficient generating step is used for extracting the edge smoothing coefficient generated by the edge smoothing processing step. The edge smoothing coefficient storing step is used for storing the edge smoothing coefficient. An input image calculation step is for processing the input image and outputting an edge-smoothed output image.
Referring to fig. 6, a flowchart of an image processing method according to the present application is shown. The image processing method 200 includes a base image synthesis step 2001, an edge smoothing processing step 2002, an edge smoothing coefficient generation step 2003, an edge smoothing coefficient storage step 2004, and an input image operation step 2005.
The base image synthesis step 2001 is a step of performing gradation processing on a series of images having a base shape. The graying processing step may be performed by a component method, a maximum value method, an average value method, a weighted average method, or the like. In this embodiment, the graying method may be a weighted average method. The base image is a publicly known image obtained by performing a graying process on a series of images having a base shape, which may be, for example, a square, a triangle, a circle, or the like. Specifically, the base image synthesizing step processes the base image into a white image including 255 gradations and a black image including 0 gradations.
The graying process is a process of converting the color image into a grayscale image, and the graying method may be a component method, a maximum value method, an average value method, a weighted average method, or the like. In the present embodiment, a preferable graying method is a component method, that is, luminance of three components (a red component, a green component, and a blue component) in a color image is taken as a grayscale value of a grayscale map. Thus, the generated gray map may be composed of the gray values of any one of the red, green and blue components, or may be composed of a weighted average of the gray values of the three components.
The edge smoothing step 2002 is a step of smoothing the image by filtering out noise of the base image using a filtering step. Specifically, the filtering step may be mean filtering. The average filtering is a filtering method in which the original pixel value is replaced by the average value of all the pixel values in the range.
Further, the filtering step included in the edge smoothing step 2002 may include various filters. In the present embodiment, the filter includes, but is not limited to, any one or a combination of gaussian filter, mean filter, median filter and adaptive filter. For example, the filtering step may include a bilateral filter, which employs a bilateral filtering method. The bilateral filtering method is a nonlinear filtering method, and when bilateral filtering processing is carried out, the position information and the gray level similarity are considered at the same time, so that the purpose of removing noise is achieved. Bilateral filtering has one more step of calculating the gaussian variance, which is a gaussian filter function based on spatial distribution, compared with gaussian filtering, and pixels farther away do not have a great influence on the pixel values on the edges near the edges. Therefore, bilateral filtering can better preserve the edges of the image.
The edge smoothing coefficient generation step 2003 is a step of processing the base image to extract an edge smoothing coefficient. Specifically, the processing procedure may be normalization processing. The use of the normalization process to extract the edge smoothing coefficient is advantageous in making the edge smoothing coefficient suitable for the input image of each situation.
Further, the edge smoothing coefficient generation step 2003 may extract an edge smoothing coefficient by compressing the base image. The compressed image can relatively completely store the original pixel matrix, and therefore, the compressed image can also be used for extracting the edge smoothing coefficient.
The edge smoothing coefficient storage step 2004 is a step of storing the normalized edge smoothing coefficient. In the edge smoothing coefficient storing step, a plurality of sets of edge smoothing coefficients may be stored simultaneously. Those skilled in the art will appreciate that complex graphics may be decomposed and/or approximated as multiple images with underlying graphics. Therefore, when performing edge smoothing processing on an input graph, storing a plurality of edge smoothing coefficients for a specific base graph in advance is advantageous for improving the efficiency of image processing. For example, the edge smoothing coefficient storing step 2004 may store the edge smoothing coefficient for a rectangle and the edge smoothing coefficient for a triangle at the same time. When the input image has a hexagonal edge contour (the hexagon can be decomposed into a plurality of triangles or into a plurality of rectangles and a plurality of triangles), the edge smoothing processing can be performed on the input image by utilizing the two sets of edge smoothing coefficients.
The input image calculation step 2005 is a step of processing the input image and outputting an output image with edges smoothed. Please refer to fig. 7, which shows a schematic structural diagram of the input image operation step provided by the present invention. In further alternative embodiments, the input image operation step 2005 further comprises an input image conversion step 21, an addressing step 22, an operation step 23 and an output image conversion step 24.
The input image conversion step 21 is a step of performing gradation processing on the input image. A white image including 255 gradations and a black image of 0 steps are obtained. The graying method may be a component method, a maximum value method, an average value method, a weighted average method, or the like. In this embodiment, the preferred graying method is a component method, and a white image including 255 grayscales and a black image of 0 level are finally obtained. The difference from the embodiment of fig. 6 is that the input image conversion step 21 is a step of performing gradation processing on an input image, and the root image synthesis step 2001 is a step of performing gradation processing on a series of images having a root shape. Note that, in order to ensure that the edge smoothing coefficients stored in the edge smoothing coefficient storage step 2004 are applied to the input image, the gradation method used in the base image synthesis step 2001 is the same as the gradation method used in the input image conversion step 21.
The addressing step 22 is a step of recognizing the input image after the graying processing and dividing the image into a limited number of basic patterns. The corresponding edge smoothing coefficients are found in the edge smoothing coefficient storage step 2004 based on the segmented base pattern.
In the operation step 23, the corresponding edge smoothing coefficient found in the addressing step 22 is used to perform smoothing processing on the input image after the graying processing.
The image conversion step 24 is a step of converting the grayscale image into a color output image.
Further, the input image operation step 2005 may be located inside or outside the driving chip.
Further, the driving chip may further include other steps. Wherein other steps may include multiple steps, and each step may be independent of each other. For example, the other step may be a gating step.
In the embodiment of the invention, the edge smoothing coefficient of the basic image is stored in advance, and the stored smoothing coefficient is directly called when the input image is processed, so that the image processing efficiency is improved.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (16)
1. An image processing system for performing image processing on an input image having a plurality of pixels arranged in a matrix, comprising:
a base image synthesizing unit configured to synthesize a plurality of base images by performing a graying process on a plurality of images having a base shape;
an edge smoothing unit, configured to perform edge smoothing on the base image;
an edge smoothing coefficient generating unit configured to extract the edge smoothing coefficient generated by the edge smoothing processing unit;
an edge smoothing coefficient storage unit for storing the edge smoothing coefficient;
an input image calculation unit configured to process the input image and output an edge-smoothed output image;
the edge smoothing processing unit filters noise of the basic image in a filtering mode, and selects preset filtering parameters in the filtering process; the filter parameters comprise a filter scale; respectively extracting edges of the basic image under each filtering scale, and fusing the edge images under different filtering scales;
the edge smoothing coefficient generating unit is used for carrying out normalization processing on the edge smoothing coefficient to obtain a series of numerical values and carrying out inverse normalization processing on the series of numerical values;
wherein the complex input image is decomposed and/or approximated as a plurality of images with underlying graphics.
2. The image processing system of claim 1, wherein the edge shape of the base image comprises a square, a triangle, or a circle.
3. The image processing system according to claim 1, wherein the base image synthesizing unit processes the base image into a white image including 255 gradations; and/or the presence of a gas in the gas,
the base image synthesizing unit processes the base image into a black image including a 0 gray scale.
4. The image processing system according to claim 1, wherein the edge smoothing unit includes a filtering unit that performs smoothing filtering processing on the base image to filter out a portion of the base image whose frequency lies within a preset frequency band.
5. The image processing system according to claim 4, wherein the filtering manner of the filtering unit is any one or a combination of gaussian filtering, mean filtering, median filtering and adaptive filtering.
6. The image processing system according to claim 1, wherein the edge smoothing coefficient generation unit is further configured to perform compression processing on the smoothed base graphics and extract corresponding edge smoothing coefficients.
7. The image processing system according to claim 1, wherein the edge smoothing coefficient storage unit is configured to store edge smoothing coefficients used in the processing by the edge smoothing processing unit, and the edge smoothing coefficient storage unit stores at least one set of edge smoothing coefficients.
8. The image processing system according to claim 1, wherein the edge smoothing coefficient storage unit is located inside or outside the driver chip.
9. The image processing system of claim 8, wherein the input image arithmetic unit is located inside the driver chip.
10. The image processing system according to claim 1, wherein the input image arithmetic unit includes:
an input image conversion unit for converting the input image into a grayscale image;
the addressing unit is used for extracting at least one group of corresponding edge smoothing coefficients from the edge smoothing coefficient storage unit according to the gray level image;
an arithmetic unit for applying the edge smoothing coefficient extracted by the addressing unit to the grayscale image;
and the output image conversion unit is used for converting the gray level image subjected to the action of the edge smoothing coefficient into an output image.
11. A display device comprising the image processing system of any one of 1 to 10.
12. An image processing method for performing image processing on an input image having a plurality of pixels arranged in a matrix, comprising:
a base image synthesis step of performing a gradation process on a plurality of images having a base shape to synthesize a plurality of base images;
an edge smoothing step of performing edge smoothing on the base image;
an edge smoothing coefficient generating step of extracting the edge smoothing coefficient generated in the edge smoothing processing step;
an edge smoothing coefficient storage step of storing the edge smoothing coefficient;
an input image calculation step of processing the input image and outputting an output image with smoothed edges;
in the step of edge smoothing, filtering noise of the basic image by adopting a filtering mode, and selecting preset filtering parameters in the filtering process; the filter parameters comprise a filter scale; respectively extracting edges of the basic image under each filtering scale, and fusing the edge images under different filtering scales;
in the step of generating the edge smooth coefficient, the edge smooth coefficient is subjected to normalization processing to obtain a series of numerical values, and the series of numerical values are subjected to inverse normalization processing;
wherein the complex input image is decomposed and/or approximated as a plurality of images with underlying graphics.
13. The image processing method according to claim 12, wherein the base image synthesizing step processes the base image into a white image including 255 gradations; and/or the presence of a gas in the gas,
the base image synthesizing step processes the base image into a black image including a 0 gray scale.
14. The image processing method according to claim 12, wherein the edge smoothing processing step includes a filtering step;
and the filtering step is used for carrying out smooth filtering processing on the basic image and filtering out the part of the basic image, the frequency of which is positioned in a preset frequency band.
15. The image processing method according to claim 14, wherein the filtering manner of the filtering step is any one or a combination of gaussian filtering, mean filtering, median filtering and adaptive filtering.
16. The image processing method of claim 12, wherein the input image operation step comprises:
an input image conversion step for converting the input image into a grayscale image;
an addressing step, which is used for extracting at least one group of corresponding edge smoothing coefficients from the edge smoothing coefficient storage step according to the gray level image;
an operation step of applying the edge smoothing coefficient extracted in the addressing step to the grayscale image;
and an output image conversion step, which is used for converting the gray level image after the edge smoothing coefficient acts into an output image.
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