CN107154233B - Image processing method and device and display control card - Google Patents
Image processing method and device and display control card Download PDFInfo
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- CN107154233B CN107154233B CN201710258673.0A CN201710258673A CN107154233B CN 107154233 B CN107154233 B CN 107154233B CN 201710258673 A CN201710258673 A CN 201710258673A CN 107154233 B CN107154233 B CN 107154233B
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- G09G3/00—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes
- G09G3/20—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters
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- G09G3/00—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes
- G09G3/20—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters
- G09G3/22—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters using controlled light sources
- G09G3/30—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters using controlled light sources using electroluminescent panels
- G09G3/32—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters using controlled light sources using electroluminescent panels semiconductive, e.g. using light-emitting diodes [LED]
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Abstract
The embodiment of the invention provides an image processing method and device and a display control card, which are used for carrying out error diffusion after gray scale reduction on each pixel point of the same input image, wherein the value of each coefficient of an error diffusion template in each error diffusion direction is different due to different pixel points, so that the false contour phenomenon in the prior art can be greatly improved, and the image display quality is improved.
Description
Technical Field
The present invention relates to the field of display technologies, and in particular, to an image processing method and apparatus capable of improving image brightness, and a display control card.
Background
With the development of science and technology, the application range of image video data is wider and wider due to the intuition of the image video data for transmitting the expression information, and the problem that how to store more complete image video information with less resource overhead follows. In order to solve the above problems, the prior art adopts an error diffusion method, wherein the principle of the error diffusion method is to quantize image pixels according to a certain scanning path and then diffuse quantization errors to adjacent unprocessed pixels in a certain manner.
However, in the prior art, errors are distributed to surrounding pixels according to a fixed proportion, and edge information of an image is not considered, so that a false contour is generated, and the image display quality is influenced.
Disclosure of Invention
Therefore, embodiments of the present invention provide an image processing method, an image processing apparatus, and a display control card, which solve the problem of generating a false contour in an image and achieve the technical effects of improving the brightness of the image and the display quality of the image.
In one aspect, an image processing method is provided, including: carrying out gray level reduction processing on the gray value of the target pixel point; calculating gradient values of the target pixel points in a plurality of error diffusion directions in a preset region, wherein the plurality of error diffusion directions are error diffusion directions in a preset error diffusion template; calculating to obtain a gradient error diffusion template according to the gradient value and the preset error diffusion template; and performing error diffusion on the decimal part of the target pixel point after the gray scale reduction treatment according to the gradient error diffusion template.
In still another aspect, an image processing method is provided, including: receiving an input image; and according to the processing method of the target pixel points, performing line-by-line traversal processing on each pixel point in the input image to obtain a processed image.
In another aspect, there is provided an image processing apparatus including: the gray level reduction processing module is used for carrying out gray level reduction processing on the gray value of the target pixel point; the gradient calculation module is used for calculating gradient values of the target pixel points in a plurality of error diffusion directions in a preset region, wherein the error diffusion directions are error diffusion directions in a preset error diffusion template; the error diffusion template generating module is used for calculating to obtain a gradient error diffusion template according to the gradient value and the preset error diffusion template; and the error diffusion module is used for performing error diffusion on the decimal part of the target pixel point subjected to the gray scale reduction treatment according to the gradient error diffusion template.
The image processing device comprises a gray level reduction processing module, a gradient calculation module, an error diffusion template generation module and an error diffusion module, wherein the gray level reduction processing module is used for performing gray level reduction processing on gray levels of target pixel points, the gradient calculation module is used for calculating gradient values of the target pixel points in a plurality of error diffusion directions in a preset area, the error diffusion directions are error diffusion directions in a preset error diffusion template, the error diffusion template generation module is used for calculating a gradient error diffusion template according to the gradient values and the preset error diffusion template, and the error diffusion module is used for performing error diffusion on a decimal part of the target pixel points after the gray level reduction processing according to the gradient error diffusion template.
In yet another aspect, a display control card is provided, adapted to be connected to an L ED display screen and comprising an image processing device, the image processing device comprising an image input module for receiving an input image, and a progressive traversal processing module for performing progressive traversal processing on each pixel point in the input image using the aforementioned image processing device to obtain a processed image.
One of the above technical solutions has the following advantages or beneficial effects: different from the prior art that errors are distributed to surrounding pixels according to a fixed proportion aiming at all image pixel points, the error diffusion template combined with the gradient direction is adopted for error diffusion in the gray scale reduction processing process, namely, the values of coefficients of the error diffusion template adopted by each pixel point of the same input image in each error diffusion direction are different due to different pixel points when error diffusion is carried out on the gray scale reduction processing, so that the false contour phenomenon existing in the prior art can be greatly improved, and the image display quality is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1A is a block diagram of an image processing apparatus according to an embodiment of the present invention;
FIG. 1B is a schematic diagram of sub-modules in the gradient calculation module of FIG. 1A;
FIG. 1C is a sub-block diagram of the error diffusion module generation module of FIG. 1A;
FIG. 2 is a block diagram of an image processing apparatus according to still another embodiment of the present invention;
fig. 3 is a schematic block diagram of a display control card according to another embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Specifically, the embodiment of the invention provides an error diffusion method with direction correlation for solving the technical problems in the prior art, so that the pseudo contour phenomenon in the prior art is greatly improved, and the picture display quality is improved, so that the L ED display screen with the inherent gray scale display precision of 16bit can achieve the gray scale display effect of 18bit or more.
Specifically, the following embodiment of the present invention will explain the implementation of the image processing method of this embodiment by taking a Floyd-Steinberg diffusion template as an example.
According to Floyd-Steinberg diffusion template, defined herein: the directions of the pixel point X (current pixel point) and the right pixel point, the right lower pixel point and the left lower pixel point are respectively marked as the horizontal direction, the vertical direction, the main diagonal direction and the sub diagonal direction; the values in the table are Value 1-7, Value 2-3, Value 3-5, Value 4-1, sumValue 1+ Value2+ Value3+ Value 4.
For any pixel point in the original image, the gradient values of the pixel point along the horizontal direction, the vertical direction, the main diagonal direction and the secondary diagonal direction are calculated firstly; according to the gradient calculation principle, the smaller the gradient value in a certain direction, the greater the possibility that the pixel point moves along the direction, so that the embodiment is designed to have a larger proportion of error diffusion along the direction; secondly, recalculating the error diffusion template of the current pixel point according to the gradient value by combining the value of the Floyd-Steinberg diffusion template, wherein the error diffusion template is called a gradient error diffusion template; then, error diffusion is performed according to the conventional error diffusion principle. The method comprises the following specific steps:
(a) and calculating gradient values Hor _ grad, Ver _ grad, MainDiag _ grad and SecondDiag _ grad of the current pixel img (i, j) along each error diffusion direction such as the horizontal direction, the vertical direction, the main diagonal direction and the secondary diagonal direction.
Pixel regions of a specified size centered on img (i, j), for example, pixel regions 3 × 3, are as follows:
in this embodiment, the gradient value is calculated in the 3 × 3 pixel region centered on img (i, j) by using the following formula:
Hor_grad＝abs[(img(i,j+1)+img(i,j-1))/2-img(i,j)]
Ver_grad＝abs[(img(i+1,j)+img(i-1,j))/2-img(i,j)]
MainDiag_grad＝abs[(img(i+1,j+1)+img(i-1,j-1))/2-img(i,j)]
SecondDiag_grad＝abs[(img(i+1,j-1)+img(i-1,j+1))/2-img(i,j)]。
in summary, the gradient value calculation method of the present embodiment is as follows: calculating an absolute value of a difference between an average value of gray values of a plurality of pixels, for example, two pixels, located on both sides of the current pixel img (i, j) in each error diffusion direction and the gray value of the current pixel img (i, j) as a gradient value in the error diffusion direction.
(b) Calculating gradient error diffusion template
(b1) Normalization of the reciprocal value of the gradient: the smaller the gradient value in a certain direction, the more likely the pixel moves in the direction, and the larger the error diffusion ratio in the direction. Where ex is increased to prevent the formula from being invalid and represents a very small value, where ex is 0.001, for example, and Thr is the value that adjusts the influence of the gradient on the diffusion template coefficients, where Thr is set to 10, for example, or other empirical values;
sum＝1/(Hor_grad+ex)+1/(Ver_grad+ex)+1/(MainDiag_grad+ex)+1/(SecondDiag_grad+ex)，
Hor＝Thr×1/(Hor_grad+ex)/sum，
Ver＝Thr×1/(Ver_grad+ex)/sum，
MainDiag＝Thr×1/(MainDiag_grad+ex)/sum，
SecondDiag＝Thr×1/(SecondDiag_grad+ex)/sum。
(b2) obtaining a gradient error diffusion template:
wherein Coef1 is (Value1+ Hor)/(Thr + sumValue),
Coef2＝(Value2+SecondDiag)/(Thr+sumValue)，
Coef3＝(Value3+Ver)/(Thr+sumValue)，
Coef4＝(Value3+MainDiag)/(Thr+sumValue)
in summary, the gradient error diffusion template calculation method of this embodiment is as follows: normalizing the reciprocal value of the gradient value in each error diffusion direction to obtain a normalized value, obtaining the sum of coefficient values in a plurality of error diffusion directions of a preset error diffusion template such as a Floyd-Steinberg diffusion template to obtain a coefficient sum value, and calculating the coefficient value of the gradient error diffusion template in the error diffusion direction according to the coefficient value and the normalized value and the coefficient sum value of the preset error diffusion template in each error diffusion direction.
(c) For an original image data, traversing pixel values of each pixel point line by line from left to right and from top to bottom or in a serpentine traversal mode, and diffusing a fractional part of a traversed current pixel point img (i, j) subjected to the gray reduction processing to surrounding pixel points according to a gradient error diffusion template, namely an updated Floyd-Steinberg error diffusion template in the progressive traversal processing process to obtain a processed image, wherein the processed image can be provided to a target display screen such as an L ED display screen for display or storage, further, a method for performing gray reduction processing on the original image data and performing error diffusion by using the gradient error diffusion template can be executed in a processor on a display control card such as a receiving card or a sending card connected to the L ED display screen, or can be executed in an upper processor, and a processor on the receiving card such as a serpentine logic device can execute gray reduction processing on the original image data and perform error diffusion processing according to the gradient error diffusion template.
In order to further clearly understand the present embodiment, the following describes the method of reducing gray scale and error diffusion in detail by taking specific examples:
suppose that 8-bit data is to be represented by a 4-bit data bandwidth, i.e., 256 (i.e., 2)8) A pixel point on the grayscale image (assuming a grayscale value of 120) is now converted to 16 (2)4) The level (which can also be understood as reducing the brightness of the image to 6.25%) is implemented by the following steps:
calculating a Value 16 × 120/256 7.5 after the 120 is expressed by 16 levels, and keeping an integer part as the pixel Value;
and (II) diffusing the error of the decimal part 0.5 to surrounding pixel points. Taking the gradient error diffusion template obtained as an example, the error of 0.5 is divided into sum (Coef1+ Coef2+ Coef3+ Coef4) parts, and diffusion is performed in accordance with the following template.
(i) pixel (i, j) represents the current pixel (for example, the gray value is 120), and the value represented by 16 levels (when the brightness is reduced to 6.25%) is pixelOut (i, j) ═ floor (16 × 120/256) ═ 7;
(ii) and diffusing the error of 0.5 to adjacent pixels at the right, left lower, right lower and right lower sides of the current pixel according to a diffusion template, wherein the specific diffusion is as follows:
pixel(i,j+1)＝pixel(i,j+1)+0.5×16×Coef1/sum，
pixel(i+1,j-1)＝pixel(i+1,j-1)+0.5×16×Coef2/sum，
pixel(i+1,j)＝pixel(i+1,j)+0.5×16×Coef3/sum，
pixel(i+1,j+1)＝pixel(i+1,j+1)+0.5×16×Coef4/sum。
finally, it should be noted that the preset error diffusion template used in the gradient error diffusion template calculation according to the embodiment of the present invention is not limited to the Floyd-Steinberg diffusion template, and is also applicable to other error diffusion templates, such as Basic diffusion template, Sierra diffusion template, Jarris-juddice-Ninke diffusion template, and the like.
a) The Basic diffusion template is as follows:
b) the Sierra diffusion template was as follows:
c) the Jarris-Judge-Ninke diffusion template is as follows:
for example, for Sierra diffusion templates, 3 × 3 pixel regions centered on the current pixel may be used to calculate the gradient value, or 5 × 5 or even larger pixel regions centered on the current pixel may be used to calculate the gradient value; in short, in the embodiment of the present invention, pixel gray gradients in a plurality of error diffusion directions defined by a preset error diffusion template are calculated, coefficient values (here, partial coefficient values may be updated, or all coefficient values) of the preset error diffusion template in the plurality of error diffusion directions are updated by using the calculated pixel gray gradients to obtain a gradient error diffusion template, then, a gray level reduction process is performed on an input image, and a fractional part of a current pixel point subjected to the gray level reduction process is diffused to surrounding pixel points according to the gradient error diffusion template, so that a processed image is obtained as an output.
Fig. 1A is a block diagram of an image processing apparatus according to an embodiment of the present invention. As shown in fig. 1A, the image processing apparatus 10 of the present embodiment includes: a gray level reduction processing module 11, a gradient calculation module 13, an error diffusion template generation module 15 and an error diffusion module 17.
The gray level reduction processing module 11 is configured to perform gray level reduction processing on the gray level value of the target pixel point; the gradient calculation module 13 is configured to calculate gradient values of the target pixel point in a plurality of error diffusion directions in a preset region, where the plurality of error diffusion directions are error diffusion directions in a preset error diffusion template; the error diffusion template generating module 15 is configured to calculate a gradient error diffusion template according to the gradient value and the preset error diffusion template; and the error diffusion module 17 is used for performing error diffusion on the decimal part of the target pixel point subjected to the gray scale reduction treatment according to the gradient error diffusion template. Moreover, the specific functional details of the gradient calculating module 13 and the error diffusion template generating module 15 may refer to the gradient value calculating manner and the gradient error diffusion template calculating manner of the foregoing embodiments, and are not described herein again; for the detailed functional details of the gray scale reduction processing module 11 and the error diffusion module 17, reference may be made to the detailed description of the gray scale reduction processing and error diffusion methods in the foregoing embodiments, which are not repeated herein.
Further, as shown in fig. 1B, the gradient calculation module 13 includes, for example: the first calculating module 131 is configured to calculate an absolute value of a difference between an average value of gray values of a plurality of pixels located at two sides of the target pixel in each error diffusion direction and the gray value of the target pixel, as a gradient value in the error diffusion direction.
As shown in fig. 1C, the error diffusion template generation module 15 includes, for example: a normalization module 151, a second calculation module 153, and a third calculation module 155. The normalization module 151 is configured to normalize the reciprocal value of the gradient value in each error diffusion direction to obtain a normalized value; the second calculating module 153 is configured to obtain a sum of coefficient values of the preset error diffusion template in multiple error diffusion directions to obtain a coefficient sum; and the third calculating module 155 is configured to calculate a coefficient value of the gradient error diffusion template in each error diffusion direction according to the coefficient value and the normalized value of the preset error diffusion template in the error diffusion direction and the coefficient sum value.
Fig. 2 is a block diagram of an image processing apparatus according to still another embodiment of the present invention. As shown in fig. 2, the image processing apparatus 20 of the present embodiment includes: an image input module 21 and a progressive traversal processing module 23; the progressive traversal processing module 23 includes a reduced gray level processing module 231, a gradient calculating module 233, an error diffusion template generating module 235, and an error diffusion module 237.
Specifically, the image input module 21 is configured to receive an input image; the progressive traversal processing module 12 is configured to perform progressive traversal processing on each pixel point in the input image, and typically performs traversal processing on each pixel point in the input image in a left-to-right and top-to-bottom scanning manner or a snake-shaped traversal manner, so as to obtain a processed image. Specifically, when the progressive traversal processing module 23 performs traversal processing on each pixel point in the input image, the currently traversed pixel point is specifically used as a target pixel point to perform the gray level reduction processing, the gradient value calculation, the gradient error diffusion module calculation and the error diffusion by the gray level reduction processing module 231, the gradient calculation module 233, the error diffusion template generation module 235 and the error diffusion module 237. The specific functions of the grayscale reduction processing module 231, the gradient calculation module 233, the error diffusion template generation module 235 and the error diffusion module 237 are the same as the functions of the modules 11, 13, 15 and 17 shown in fig. 1A, 1B and 1C, and are not described herein again.
It should be noted that the image processing apparatus 10 shown in fig. 1A to 1C and the image processing apparatus 20 shown in fig. 2 are implemented by a plurality of software modules stored in a memory, for example, and the software modules can be executed by a processor in an upper computer or a processor on a display control card such as a transmitting card or a receiving card.
Referring to fig. 3, a schematic block diagram of a display control card in an embodiment of the present invention is shown, in fig. 3, a display control card 30 in this embodiment is suitable for connecting L ED display screens and includes an image processing apparatus 31, the image processing apparatus 31 in this embodiment is used for performing a gray scale reduction process and an error diffusion process of a reduced-gray-scale decimal portion on an input image to obtain a processed image, which may be the image processing apparatus 10 shown in fig. 1A-1C or the image processing apparatus 20 shown in fig. 2, as for the display control card 30 in this embodiment, it may be a sending card or a receiving card, and each block in the image processing apparatus 31 for implementing the gray scale reduction process and the error diffusion process may be a software block executed on a programmable logic device, such as an FPGA, on the sending card or the receiving card.
In summary, the image processing method, the image processing apparatus, and the display control card according to the embodiments of the present invention are different from the prior art in that errors are distributed to surrounding pixels according to a fixed ratio for all image pixel points, and an error diffusion template in a gradient direction is used to perform error diffusion in the gray scale reduction process, that is, values of coefficients of the error diffusion template in each error diffusion direction of each pixel point of the same input image are different for different pixel points when error diffusion is performed after the gray scale reduction process, so that a false contour phenomenon existing in the prior art can be greatly improved, and the image display quality can be improved.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and the actual implementation may have another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (12)
1. An image processing method, comprising:
carrying out gray level reduction processing on the gray value of the target pixel point;
calculating gradient values of the target pixel points in a plurality of error diffusion directions in a preset region, wherein the plurality of error diffusion directions are error diffusion directions in a preset error diffusion template;
calculating to obtain a gradient error diffusion template according to the gradient value and the preset error diffusion template;
performing error diffusion on the decimal part of the target pixel point after the gray scale reduction treatment according to the gradient error diffusion template;
the preset area is an area with the target pixel point as a center;
wherein the calculating the gradient values of the target pixel points in a plurality of error diffusion directions in a preset region comprises:
and calculating the absolute value of the difference between the average value of the gray values of a plurality of pixels positioned at two sides of the target pixel in each error diffusion direction and the gray value of the target pixel to be used as the gradient value in the error diffusion direction.
2. An image processing method, comprising:
carrying out gray level reduction processing on the gray value of the target pixel point;
calculating gradient values of the target pixel points in a plurality of error diffusion directions in a preset region, wherein the plurality of error diffusion directions are error diffusion directions in a preset error diffusion template;
calculating to obtain a gradient error diffusion template according to the gradient value and the preset error diffusion template;
performing error diffusion on the decimal part of the target pixel point after the gray scale reduction treatment according to the gradient error diffusion template;
wherein, the calculating the gradient error diffusion template according to the gradient value and the preset error diffusion template comprises:
normalizing the reciprocal value of the gradient value in each error diffusion direction to obtain a normalized value;
obtaining the sum of the coefficient values of the preset error diffusion template in the multiple error diffusion directions to obtain a coefficient sum value;
and calculating the coefficient value of the gradient error diffusion template in the error diffusion direction according to the coefficient value and the normalization value of the preset error diffusion template in each error diffusion direction and the coefficient sum value.
3. An image processing method, comprising:
receiving an input image;
the method according to claim 1 or 2, performing a line-by-line traversal processing on each pixel point in the input image to obtain a processed image.
4. The image processing method of claim 3, wherein the values of the coefficients of the gradient error diffusion templates used for different pixels in the input image in the plurality of error diffusion directions are different.
5. The image processing method of claim 4, wherein the line-by-line traversal comprises a left-to-right and top-to-bottom scanning manner, or a serpentine traversal manner.
6. An image processing apparatus characterized by comprising:
the gray level reduction processing module is used for carrying out gray level reduction processing on the gray value of the target pixel point;
the gradient calculation module is used for calculating gradient values of the target pixel points in a plurality of error diffusion directions in a preset region, wherein the error diffusion directions are error diffusion directions in a preset error diffusion template;
the error diffusion template generating module is used for calculating to obtain a gradient error diffusion template according to the gradient value and the preset error diffusion template;
the error diffusion module is used for performing error diffusion on the decimal part of the target pixel point subjected to the gray scale reduction treatment according to the gradient error diffusion template;
the preset area is an area with the target pixel point as a center;
the gradient calculation module comprises a first calculation module, and the first calculation module is used for calculating an absolute value of a difference between an average value of gray values of a plurality of pixels located at two sides of the target pixel in each error diffusion direction and a gray value of the target pixel as a gradient value in the error diffusion direction.
7. An image processing apparatus characterized by comprising:
the gray level reduction processing module is used for carrying out gray level reduction processing on the gray value of the target pixel point;
the gradient calculation module is used for calculating gradient values of the target pixel points in a plurality of error diffusion directions in a preset region, wherein the error diffusion directions are error diffusion directions in a preset error diffusion template;
the error diffusion template generating module is used for calculating to obtain a gradient error diffusion template according to the gradient value and the preset error diffusion template;
the error diffusion module is used for performing error diffusion on the decimal part of the target pixel point subjected to the gray scale reduction treatment according to the gradient error diffusion template;
wherein the error diffusion template generating module comprises:
the normalization module is used for normalizing the reciprocal value of the gradient value in each error diffusion direction to obtain a normalized value;
the second calculation module is used for obtaining the sum of the coefficient values of the preset error diffusion template in the multiple error diffusion directions to obtain a coefficient sum value;
and the third calculating module is used for calculating the coefficient value of the gradient error diffusion template in the error diffusion direction according to the coefficient value and the normalization value of the preset error diffusion template in each error diffusion direction and the coefficient sum value.
8. An image processing apparatus characterized by comprising:
the image input module is used for receiving an input image;
a progressive traversal processing module, configured to perform progressive traversal processing on each pixel point in the input image by using the image processing apparatus according to claim 6 or 7, so as to obtain a processed image.
9. The image processing apparatus as claimed in claim 8, wherein the values of the coefficients of the gradient error diffusion templates used for different pixels in the input image are different in the plurality of error diffusion directions.
10. The image processing apparatus of claim 8, wherein the progressive traversal processing module is configured to employ a left-to-right and top-to-bottom scanning mode, or a serpentine traversal mode.
11. A display control card, characterized in that, the display control card is connected with a display screen, and the display control card comprises the image processing device of claim 6 or 7.
12. The utility model provides a display control card which characterized in that, display control card connects the display screen, display control card includes:
the image input module is used for receiving an input image;
a progressive traversal processing module, configured to perform progressive traversal processing on each pixel point in the input image by using the image processing apparatus according to claim 6 or 7, so as to obtain a processed image.
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