CN117911300A - Method and device for processing image - Google Patents
Method and device for processing image Download PDFInfo
- Publication number
- CN117911300A CN117911300A CN202311797704.1A CN202311797704A CN117911300A CN 117911300 A CN117911300 A CN 117911300A CN 202311797704 A CN202311797704 A CN 202311797704A CN 117911300 A CN117911300 A CN 117911300A
- Authority
- CN
- China
- Prior art keywords
- brightness
- pixel
- value
- image
- processed
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 73
- 238000012545 processing Methods 0.000 title claims abstract description 54
- 230000002708 enhancing effect Effects 0.000 claims abstract description 23
- 230000011218 segmentation Effects 0.000 claims description 45
- 238000006243 chemical reaction Methods 0.000 claims description 20
- 239000003086 colorant Substances 0.000 claims description 18
- 239000011159 matrix material Substances 0.000 claims description 14
- 230000008859 change Effects 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 10
- 239000000758 substrate Substances 0.000 claims 3
- 230000000694 effects Effects 0.000 abstract description 7
- 230000008569 process Effects 0.000 description 10
- 238000010586 diagram Methods 0.000 description 9
- 238000004891 communication Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 230000003287 optical effect Effects 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000000926 separation method Methods 0.000 description 3
- 239000000835 fiber Substances 0.000 description 2
- 238000003672 processing method Methods 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 238000012896 Statistical algorithm Methods 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Landscapes
- Image Processing (AREA)
Abstract
The invention discloses a method and a device for processing images, and relates to the technical field of image processing. One embodiment of the method comprises the following steps: calculating a brightness statistic value according to the brightness characteristic value of each pixel in the image to be processed; according to the brightness statistic value, adjusting the brightness characteristic value of each pixel, and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value; thereby enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value. The embodiment of the invention improves the definition degree of the contrast of the processed image and improves the processing effect of enhancing the contrast of the image.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to a method and an apparatus for processing an image.
Background
With the development of display technology, in order to make a display screen closer to a natural scene, the viewing sense is better, and the requirement on the quality of a displayed image is higher and higher, wherein the image contrast is an important index for influencing the quality of the image.
At present, a histogram equalization technology is generally utilized to change a gray level histogram of an original image from a certain gray level interval in a comparative set to be uniformly distributed in all gray level ranges so as to enhance the contrast of the image, and the existing method has the problems of detail loss and noise introduction of the processed image caused by poor fineness of the contrast of the processed image, so that the authenticity and definition of the image with enhanced contrast are affected.
Disclosure of Invention
In view of this, an embodiment of the present invention provides a method and an apparatus for processing an image, which can calculate a luminance statistic value according to a luminance feature value of each pixel in an image to be processed; according to the brightness statistic value, adjusting the brightness characteristic value of each pixel, and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value; thereby enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value. The embodiment of the invention improves the definition degree of the contrast of the processed image and improves the processing effect of enhancing the contrast of the image.
To achieve the above object, according to one aspect of the embodiments of the present invention, there is provided a method of processing an image, including: determining pixel characteristics corresponding to each pixel of an image to be processed in a color space, wherein the pixel characteristics comprise a brightness characteristic value and a chromaticity characteristic value; calculating a brightness statistic value of the image to be processed according to the brightness characteristic value of each pixel contained in the image to be processed; according to the brightness statistic value, adjusting the brightness characteristic value of each pixel of the image to be processed, and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value; and enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value.
Optionally, the determining the pixel characteristic corresponding to each pixel of the image to be processed in the color space includes: for each pixel of the image to be processed, acquiring color pixel values corresponding to three basic colors of pixel data of the pixel in a color space; and converting the color pixel values corresponding to the three basic colors into a luminance characteristic value and a chrominance characteristic value based on a first preset conversion coefficient matrix.
Optionally, the enhancing the contrast of the image to be processed according to the adjusted luminance feature value and the adjusted chrominance feature value includes: converting the adjusted brightness characteristic value and the adjusted chromaticity characteristic value corresponding to each pixel into adjusted color pixel values corresponding to three basic colors based on a second preset conversion coefficient matrix; and displaying an enhanced image for the image to be processed based on the adjusted color pixel values.
Optionally, the calculating the brightness statistic of the image to be processed includes: calculating a first brightness statistic value of the image to be processed according to the brightness characteristic value of each pixel in the image to be processed; acquiring a second brightness statistic value of an adjacent frame image corresponding to the image to be processed; calculating a difference between the first luminance statistic and the second luminance statistic; taking the second brightness statistical value as the brightness statistical value of the image to be processed under the condition that the difference value is lower than a set brightness change threshold value; and taking the first brightness statistical value as the brightness statistical value of the image to be processed under the condition that the difference value is not lower than a set brightness change threshold value.
Optionally, the adjusting the brightness characteristic value of each pixel of the image to be processed includes: acquiring a minimum brightness value and a maximum brightness value in brightness characteristic values of the image to be processed; according to the minimum brightness value, the maximum brightness value and the brightness initial statistical value of the image to be processed, calculating a first brightness value of a dark area demarcation point and a second brightness value of a bright area demarcation point of the image to be processed; determining a plurality of brightness segmentation intervals of the image to be processed based on the minimum brightness value, the maximum brightness value, the brightness initial statistical value, the first brightness value and the second brightness value, wherein each brightness segmentation interval is correspondingly provided with a statistical parameter; for each pixel of the image to be processed, performing: determining a target brightness segmentation interval to which the brightness characteristic value of the pixel belongs and a statistical parameter corresponding to the target brightness segmentation interval from a plurality of brightness segmentation intervals; and calculating the target brightness value of the pixel according to the brightness characteristic value of the pixel, the statistical parameter corresponding to the target brightness segmentation interval and the first brightness value.
Optionally, the adjusting the brightness characteristic value of each pixel of the image to be processed further includes: for each pixel of each row of the image to be processed, executing steps N1-N2: n1: selecting a set number of pixels in a row where the pixels are located according to a preset direction by taking the pixels as a starting point, forming a pixel group by the set number of pixels, and determining key pixels of the pixel group; n2: calculating the sharpening brightness value of the key pixel based on the brightness characteristic value of each pixel in the pixel group and a preset position weight; and determining the optimized brightness value of the key pixel by combining the brightness characteristic value of the key pixel and the sharpened brightness value aiming at each key pixel in the image to be processed.
Optionally, the adjusting the brightness characteristic value of each pixel of the image to be processed further includes: under the condition that the set number is a plurality of set numbers, determining target key pixels which are overlapped in the key pixels corresponding to the plurality of set numbers; and further optimizing the optimized brightness value of the target key pixel based on the optimized brightness value corresponding to the target key pixel obtained by each set quantity and the preset weight corresponding to each set quantity.
Optionally, the adjusting the chrominance feature value of the pixel based on the adjusted luminance feature value includes: and for each pixel of the image to be processed, determining the chromaticity characteristic value after the pixel adjustment by utilizing the ratio of the brightness characteristic value after the pixel adjustment to the original brightness characteristic value of the pixel and the original chromaticity characteristic value of the pixel.
In order to achieve the above object, according to a second aspect of an embodiment of the present invention, there is provided an apparatus for processing an image, comprising: the method comprises the steps of acquiring a characteristic module, determining brightness module and adjusting pixel module; wherein,
The image processing module is used for processing the image to be processed, and acquiring a characteristic module, which is used for determining a pixel characteristic corresponding to each pixel of the image to be processed in a color space, wherein the pixel characteristic comprises a brightness characteristic value and a chromaticity characteristic value;
The brightness determining module is used for calculating the brightness statistic value of the image to be processed according to the brightness characteristic value of the image to be processed;
The pixel adjusting module is used for adjusting the brightness characteristic value of each pixel of the image to be processed according to the brightness statistic value and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value; and enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value.
Optionally, the device for processing the image is configured to determine a pixel feature corresponding to each pixel of the image to be processed in a color space, and includes: for each pixel of the image to be processed, acquiring color pixel values corresponding to three basic colors of pixel data of the pixel in a color space; and converting the color pixel values corresponding to the three basic colors into a luminance characteristic value and a chrominance characteristic value based on a first preset conversion coefficient matrix.
Optionally, the device for processing an image is configured to enhance the contrast of the image to be processed according to the adjusted luminance feature value and the adjusted chrominance feature value, and includes: converting the adjusted brightness characteristic value and the adjusted chromaticity characteristic value corresponding to each pixel into adjusted color pixel values corresponding to three basic colors based on a second preset conversion coefficient matrix; and displaying an enhanced image for the image to be processed based on the adjusted color pixel values.
Optionally, the device for processing an image is configured to calculate a brightness statistic of the image to be processed, and includes: calculating a first brightness statistic value of the image to be processed according to the brightness characteristic value of each pixel in the image to be processed; acquiring a second brightness statistic value of an adjacent frame image corresponding to the image to be processed; calculating a difference between the first luminance statistic and the second luminance statistic; taking the second brightness statistical value as the brightness statistical value of the image to be processed under the condition that the difference value is lower than a set brightness change threshold value; and taking the first brightness statistical value as the brightness statistical value of the image to be processed under the condition that the difference value is not lower than a set brightness change threshold value.
Optionally, the device for processing an image is configured to adjust a brightness characteristic value of each pixel of the image to be processed, and includes: acquiring a minimum brightness value and a maximum brightness value in brightness characteristic values of the image to be processed; according to the minimum brightness value, the maximum brightness value and the brightness initial statistical value of the image to be processed, calculating a first brightness value of a dark area demarcation point and a second brightness value of a bright area demarcation point of the image to be processed; determining a plurality of brightness segmentation intervals of the image to be processed based on the minimum brightness value, the maximum brightness value, the brightness initial statistical value, the first brightness value and the second brightness value, wherein each brightness segmentation interval is correspondingly provided with a statistical parameter; for each pixel of the image to be processed, performing: determining a target brightness segmentation interval to which the brightness characteristic value of the pixel belongs and a statistical parameter corresponding to the target brightness segmentation interval from a plurality of brightness segmentation intervals; and calculating the target brightness value of the pixel according to the brightness characteristic value of the pixel, the statistical parameter corresponding to the target brightness segmentation interval and the first brightness value.
Optionally, the device for processing an image is configured to adjust a brightness characteristic value of each pixel of the image to be processed, and further includes: for each pixel of each row of the image to be processed, executing steps N1-N2: n1: selecting a set number of pixels in a row where the pixels are located according to a preset direction by taking the pixels as a starting point, forming a pixel group by the set number of pixels, and determining key pixels of the pixel group; n2: calculating the sharpening brightness value of the key pixel based on the brightness characteristic value of each pixel in the pixel group and a preset position weight; and determining the optimized brightness value of the key pixel by combining the brightness characteristic value of the key pixel and the sharpened brightness value aiming at each key pixel in the image to be processed.
Optionally, the means for adjusting the processed image is configured to adjust a brightness characteristic value of each pixel of the image to be processed, and further includes: under the condition that the set number is a plurality of set numbers, determining target key pixels which are overlapped in the key pixels corresponding to the plurality of set numbers; and further optimizing the optimized brightness value of the target key pixel based on the optimized brightness value corresponding to the target key pixel obtained by each set quantity and the preset weight corresponding to each set quantity.
Optionally, the device for processing an image is configured to adjust a chromaticity eigenvalue of the pixel based on the adjusted luminance eigenvalue, and includes: and for each pixel of the image to be processed, determining the chromaticity characteristic value after the pixel adjustment by utilizing the ratio of the brightness characteristic value after the pixel adjustment to the original brightness characteristic value of the pixel and the original chromaticity characteristic value of the pixel.
In order to achieve the above object, according to a third aspect of an embodiment of the present invention, there is provided an electronic apparatus that processes an image, comprising: one or more processors; and a storage means for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the method of processing an image as described in any of the methods of processing an image above.
To achieve the above object, according to a fourth aspect of embodiments of the present invention, there is provided a computer-readable medium having stored thereon a computer program, characterized in that the program, when executed by a processor, implements a method as described in any one of the above methods of processing an image.
To achieve the above object, according to a fifth aspect of an embodiment of the present invention, there is provided a chip implementing the method of any one of the methods of processing an image as described in the first aspect.
To achieve the above object, according to a sixth aspect of embodiments of the present invention, there is provided computer software implementing the method according to any one of the methods of processing an image according to the first aspect.
One embodiment of the above invention has the following advantages or benefits: calculating a brightness statistic value according to the brightness characteristic value of each pixel in the image to be processed; according to the brightness statistic value, adjusting the brightness characteristic value of each pixel, and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value; thereby enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value. The embodiment of the invention improves the definition degree of the contrast of the processed image and improves the processing effect of enhancing the contrast of the image.
Further effects of the above-described non-conventional alternatives are described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a flow chart of a method of processing an image according to an embodiment of the present invention;
FIG. 2 is a schematic diagram showing a plurality of brightness distribution intervals of an image according to an embodiment of the present invention;
FIG. 3 is a flow chart of processing an image according to one embodiment of the present invention;
FIG. 4 is a flow chart of another process image provided by an embodiment of the present invention;
FIG. 5 is a schematic diagram of an apparatus for processing an image according to an embodiment of the present invention;
FIG. 6 is an exemplary system architecture diagram in which embodiments of the present invention may be applied;
fig. 7 is a schematic diagram of a computer system suitable for use in implementing an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding, and are to be considered merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
As shown in fig. 1, an embodiment of the present invention provides a method of processing an image, which may include the steps of:
Step S101: and determining pixel characteristics corresponding to each pixel of the image to be processed in a color space, wherein the pixel characteristics comprise a brightness characteristic value and a chromaticity characteristic value.
Specifically, in the embodiment of the present invention, the image to be processed is an image subjected to contrast enhancement by using the method of the embodiment of the present invention.
Further, a pixel characteristic corresponding to each pixel of the image to be processed in a color space is determined, wherein the pixel characteristic comprises a luminance characteristic value and a chrominance characteristic value. In an embodiment of the present invention, it may be determined that the pixel characteristics include luminance characteristic values (e.g., Y component of YUV space) and chrominance characteristic values (U component, V component of YUV space) by extracting pixel characteristics of a YUV color space (i.e., color-luminance separated color space) of an image.
Step S102: and calculating the brightness statistic value of the image to be processed according to the brightness characteristic value of each pixel contained in the image to be processed.
Specifically, according to the brightness characteristic value of each pixel in the image, calculating the brightness statistic value of the image to be processed. The luminance statistics value can be a luminance average value, a luminance median, a luminance percentile and the like, and the specific calculation method of the luminance statistics value is not limited.
Further, the methods for calculating the brightness statistics value of the image to be processed in the invention are two methods:
the first method is as follows: and acquiring a brightness characteristic value corresponding to each pixel included in the graph to be processed, and calculating by using a statistical algorithm (such as an average value, a median, a percentile algorithm and the like) based on the brightness value of each pixel to obtain a brightness statistical value of the graph to be processed.
The second method is as follows: the luminance statistics value of the image to be processed is determined by combining the luminance statistics values of adjacent frame images of the image to be processed, for example, a previous frame image of the image to be processed in time sequence, it can be understood that in many application scenarios, a plurality of frame images are usually continuously shot, and if the image to be processed is an nth frame image, the adjacent frame image can be an N-1 th frame image. Specifically, a first luminance statistic Y N of the nth frame image is calculated, and a second luminance statistic Y N-1 of the N-1 th frame image is calculated; and calculating a difference y_diff between the first luminance statistic and the second luminance statistic as shown in formula (1); wherein the difference is an absolute value.
YN-YN-1＝Y_Diff (1)
Taking the second brightness statistical value Y N-1 as the brightness statistical value of the image to be processed under the condition that the difference value Y_Diff is lower than a set brightness change threshold value; otherwise, the first brightness statistic Y N is used as the brightness statistic of the image to be processed. That is, the calculating the brightness statistic of the image to be processed includes: calculating a first brightness statistic value of the image to be processed according to the brightness characteristic value of each pixel in the image to be processed; acquiring a second brightness statistic value of an adjacent frame image corresponding to the image to be processed; calculating a difference between the first luminance statistic and the second luminance statistic; taking the second brightness statistical value as the brightness statistical value of the image to be processed under the condition that the difference value is lower than a set brightness change threshold value; and taking the first brightness statistical value as the brightness statistical value of the image to be processed under the condition that the difference value is not lower than a set brightness change threshold value.
Therefore, the embodiment of the invention determines the brightness statistic value of the image to be processed through the image brightness statistic value of the adjacent frames, and improves the accuracy and the effectiveness of determining the brightness statistic value of the image to be processed, thereby improving the accuracy degree of brightness corresponding to the contrast ratio determined later.
Step S103: according to the brightness statistic value, adjusting the brightness characteristic value of each pixel of the image to be processed, and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value; and enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value.
Specifically, based on the brightness statistic value (namely, the brightness initial statistic value) of the image to be processed, calculating a corresponding adjusted brightness value for each pixel of the image to be processed according to a set policy, and replacing the original brightness value with the adjusted brightness value, so that the contrast of the image to be processed is enhanced by combining the adjusted chromaticity characteristic value based on the adjusted brightness characteristic value of each pixel.
In an embodiment of the present invention, the method for calculating the adjusted luminance feature value of each pixel of the image to be processed according to the luminance statistic includes the following steps:
The first method is as follows: and determining a brightness segmentation interval of a certain image to be processed, and determining the brightness segmentation interval to which the pixel belongs and statistical parameters of the interval aiming at each pixel of the image to be processed, thereby further calculating the adjusted brightness characteristic value of the pixel.
Specifically, there are two methods for obtaining the minimum luminance value min and the maximum luminance value max from the luminance characteristic value of the image to be processed:
The first method is as follows: the minimum luminance value and the maximum luminance value can be obtained through a luminance histogram obtained by luminance characteristic values corresponding to an image to be processed (wherein the histogram is a statistical report chart, and a series of vertical stripes or line segments with different heights are used for representing the data distribution, generally, the horizontal axis is used for representing the data type, the vertical axis is used for representing the distribution, the horizontal axis of the luminance histogram of the image is the luminance of pixels, the luminance histogram of the image is obtained through counting the luminance values of all pixels of the image to be processed, various luminance statistical values of the image are represented in a histogram mode, for example, the luminance values are from left to right, the luminance values are from low to high, when the luminance histogram is from left to right, the luminance value with the accumulated number of pixels N (for example, any number in 1-10) is selected from the leftmost side of the luminance histogram of the image as the minimum luminance value min, and the luminance value with the accumulated number of pixels M (for example, any number in 1-10) is selected from the rightmost side of the histogram as the maximum luminance value max.
The second method is as follows: and directly selecting a minimum brightness value min and a maximum brightness value max from brightness characteristic values of all pixels contained in the image to be processed.
Further, according to the minimum brightness value, the maximum brightness value and the brightness initial statistical value of the image to be processed, calculating a first brightness value of a dark area demarcation point and a second brightness value of a bright area demarcation point of the image to be processed; taking the average value as the luminance statistic value as an example, for example, the luminance initial statistic value of the image to be processed is represented by Y average as an example, the following formula (2) can be used to calculate the first luminance value of the dark area demarcation point and the second luminance value of the bright area demarcation point:
wherein b represents a first luminance value of a dark region (black) demarcation point and a second luminance value of a w bright region (white) demarcation point; alpha b、αw represents a coefficient within a range of values (0, 1), and the specific value of the coefficient can be set according to the actual application scene.
Further, the midpoint mb representing min and b, and the midpoint mw of max and w are calculated using formula (3) as follows:
Further, determining a plurality of brightness segmentation intervals of the image to be processed based on the calculated b and w and the calculated mb and mw, wherein each brightness segmentation interval is correspondingly provided with a statistical parameter; the statistical parameter is represented by k in the following expression (4):
As shown in expression (4), each row in the expression represents one luminance segment interval, and the corresponding statistical parameter k. According to which brightness segment interval the original brightness characteristic value of the pixel belongs to, a corresponding k value can be calculated, for example, y < min, and the statistical parameter k is 0; for another example, min < Y < mb, then k=1- (mb-min)/Y average; that is, based on the minimum brightness value, the maximum brightness value, the brightness initial statistical value, the first brightness value and the second brightness value, a plurality of brightness segmentation intervals of the image to be processed are determined, wherein each brightness segmentation interval is correspondingly provided with a statistical parameter.
fig. 2 shows that a certain image is based on min, max, b, w and a plurality of brightness segmentation intervals of mb and mw, as can be seen from fig. 2, the slopes of the segments of different brightness segmentation intervals are different, that is, the statistical parameter k is different, that is, each brightness segmentation interval is correspondingly provided with a statistical parameter, and the target brightness value of the pixel is determined through the plurality of brightness segmentation intervals, so that the refinement degree of the adjusted pixel is improved to a greater extent, and the definition, fineness and overall effect of image contrast enhancement are improved.
Further, for each pixel of the image to be processed, performing: determining a target brightness segmentation interval to which the brightness characteristic value of the pixel belongs and a statistical parameter corresponding to the target brightness segmentation interval from a plurality of brightness segmentation intervals; and calculating the target brightness value of the pixel according to the brightness characteristic value of the pixel, the statistical parameter corresponding to the target brightness segmentation interval and the first brightness value.
For example, a method of calculating a target luminance value of a pixel is as shown in formula (5):
Yout＝k*Yin+b (5)
Wherein Y out represents the target luminance value of a pixel, and Y in represents the original luminance value of the pixel; k represents the k value corresponding to the luminance segmentation interval to which the pixel belongs, and b represents the first luminance value of the dark area (black) demarcation point, it can be understood that the k value is calculated by the range to which y (i.e., the original luminance value of the pixel) belongs in the expression (4), and according to the expression (4), if a certain pixel: for example, if the original luminance value Y of the pixel a is smaller than b and greater than or equal to mb, the value of k is calculated by using 1+ (b-mb)/Y average, and then the target luminance value of the pixel a is obtained by using formula (5). Similarly, a corresponding operation is performed for each pixel of the image to be processed to obtain a target brightness value, where the target brightness value is the brightness characteristic value of the adjusted pixel.
That is, the adjusting the brightness characteristic value of each pixel of the image to be processed includes: acquiring a minimum brightness value and a maximum brightness value in brightness characteristic values of the image to be processed; according to the minimum brightness value, the maximum brightness value and the brightness initial statistical value of the image to be processed, calculating a first brightness value of a dark area demarcation point and a second brightness value of a bright area demarcation point of the image to be processed; determining a plurality of brightness segmentation intervals of the image to be processed based on the minimum brightness value, the maximum brightness value, the brightness initial statistical value, the first brightness value and the second brightness value, wherein each brightness segmentation interval is correspondingly provided with a statistical parameter; for each pixel of the image to be processed, performing: determining a target brightness segmentation interval to which the brightness characteristic value of the pixel belongs and a statistical parameter corresponding to the target brightness segmentation interval from a plurality of brightness segmentation intervals; and calculating the target brightness value of the pixel according to the brightness characteristic value of the pixel, the statistical parameter corresponding to the target brightness segmentation interval and the first brightness value.
The second method is as follows: a plurality of key pixels are determined using one or more high pass filters, and a sharpening process is performed on the key pixels.
In particular, the edge information of the image can represent the texture information of the image, so that the image retains more detail information, and the brightness of the image is sharpened.
Acquiring pixels at a first row and a first column in the image to be processed as starting pixels, and performing traversal on each pixel of the image to be processed by using one or more high-pass filters to determine edge pixels needing sharpening, wherein in one embodiment of the invention, two high-pass filters are adopted for execution; in the case of using two high-pass filters, for each pixel of each line of the image to be processed, performing: the first high-pass filter adopts 5 pixels to carry out pixel processing, namely, a set number of pixels are selected from the row where the pixels are located, the set number of pixels form a pixel group, and key pixels of the pixel group are determined; the method of the first high-pass filter is as shown in formula (6):
wherein,
Assume thatIt is known from formula (6) that the key pixel is the 3 rd pixel in the pixel group consisting of 5 pixels, where y 0～y4 represents the original luminance feature value of each pixel in one pixel group or the target feature value calculated through the luminance segment interval by the first method.
Further, the second high-pass filter uses 9 pixels as a set number of pixels to form a pixel group for pixel processing, and determines key pixels of the pixel group, and the method of the second high-pass filter is as shown in formula (7):
wherein,
Assume that
According to formula (7), in the second high-pass filter, the key pixel is the 5 th pixel in a pixel group formed by 9 pixels, by combining the first high-pass filter and the second high-pass filter, traversing each pixel of each line of the image according to a preset direction (for example, each line from top to bottom and each line from left to right), a plurality of key pixels with edge characteristics or coincident key pixels can be filtered, so that sharpening processing is further performed on the key pixels, and the contrast enhancement effect on the image is further improved; the number of the high-pass filters and the specific numerical values of the set number are not limited in the invention.
Further, in combination with Y out1 of the output of the first high-pass filter and Y out2 of the output of the second high-pass filter, the calculated sharpening luminance value of the key pixel is:
Y＝Y1+ Yout1*β+ Yout2*(1-β) (8)
Wherein Y1 represents an original brightness value of a key pixel or an adjusted target brightness value calculated by a brightness segmentation interval method; beta is a preset weight, for example, a value between 0.3 and 0.7. The optimized luminance value Y of the target key pixel is further optimized based on the optimized luminance value (Y out1、Yout2) corresponding to the target key pixel obtained by each set number and the preset weight beta or (1-beta) corresponding to each set number. And determining an optimized luminance value Y of each key pixel in the image to be processed by combining the luminance characteristic value (the original luminance characteristic value Y1 of the pixel or the target luminance value Y1 determined by a luminance segmentation method) of the key pixel and the sharpened luminance value. That is, the adjusting the brightness characteristic value of each pixel of the image to be processed further includes: for each pixel of each row of the image to be processed, executing steps N1-N2: n1: selecting a set number of pixels in a row where the pixels are located according to a preset direction by taking the pixels as a starting point, forming a pixel group by the set number of pixels, and determining key pixels of the pixel group; n2: calculating the sharpening brightness value of the key pixel based on the brightness characteristic value of each pixel in the pixel group and a preset position weight; and determining the optimized brightness value of the key pixel by combining the brightness characteristic value of the key pixel and the sharpened brightness value aiming at each key pixel in the image to be processed.
Further, the adjusting the brightness characteristic value of each pixel of the image to be processed further includes: under the condition that the set number is a plurality of set numbers, determining target key pixels which are overlapped in the key pixels corresponding to the plurality of set numbers; and further optimizing the optimized brightness value of the target key pixel based on the optimized brightness value corresponding to the target key pixel obtained by each set quantity and the preset weight corresponding to each set quantity. Specifically, in the embodiment of the present invention, the setting number is 5 and the setting number is 9 are respectively exemplified, that is, in the case that the setting number is a plurality of setting numbers, the optimal luminance value of the target key pixel overlapped in each of the key pixels corresponding to the plurality of setting numbers is determined as Y in the formula (8).
The third method is as follows: the sharpening process is further performed by the second method, in combination with the first method, on the basis of the first method calculating the enhanced contrast of the target luminance value for each pixel.
Further, the chromaticity characteristic value of the pixel is adjusted based on the adjusted luminance characteristic value. The adjusting the chromaticity characteristic value of the pixel based on the adjusted luminance characteristic value includes: and for each pixel of the image to be processed, determining the chromaticity characteristic value after the pixel adjustment by utilizing the ratio of the brightness characteristic value after the pixel adjustment to the original brightness characteristic value of the pixel and the original chromaticity characteristic value of the pixel.
Specifically, as shown in formula (9), the adjusted chrominance feature values U out and V out of a certain pixel are calculated by using the ratio of the adjusted luminance feature value of the pixel to the original luminance feature value of the pixel, i.e., Y out/Yin, in combination with the coefficients δ and λ.
Further, the contrast of the image to be processed is enhanced according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value. The adjusted luminance characteristic value may be a target luminance value, a sharpened luminance value combined with the target luminance value, or the like. Therefore, through multi-dimension brightness adjustment based on pixels and corresponding chromaticity adjustment, the definition degree of the contrast of the enhanced image is improved, the problems of detail loss and noise introduction of the processed image caused by poor definition of the contrast of the processed image in the existing method are solved, and the authenticity and definition of the image with enhanced contrast are improved.
As shown in fig. 3, an embodiment of the present invention provides a process for processing an image, which may include the following steps:
Step S201: for each pixel of the image to be processed, acquiring color pixel values corresponding to three basic colors of pixel data of the pixel in a color space; and converting the color pixel values corresponding to the three basic colors into a luminance characteristic value and a chrominance characteristic value based on a first preset conversion coefficient matrix.
Specifically, in an embodiment of the present invention, the method for determining the pixel characteristics corresponding to each pixel of the image to be processed in the color space (where the pixel characteristics include a luminance characteristic value and a chrominance characteristic value) may be directly obtaining the luminance characteristic value and the chrominance characteristic value corresponding to the color-luminance separation color space (YUV space), or may be obtained through RGB space conversion of the pixel. And under the condition of being obtained through RGB space conversion, converting color pixel values corresponding to three colors (RGB) in the primary color space (RGB space) into brightness characteristic values and chromaticity characteristic values corresponding to the pixels in the color-brightness separation color space (YUV space) based on a first preset conversion coefficient matrix. The conversion expression is as follows:
wherein, RGB represents the color pixel value corresponding to three basic colors of a certain pixel in RGB color space, YUV represents the brightness characteristic value and chromaticity characteristic value corresponding to a certain pixel color-brightness separation color space (YUV space).
For the first preset conversion coefficient matrix, the value of one conversion coefficient adopted in the embodiment of the invention is/>
That is, determining a pixel characteristic corresponding to each pixel of the image to be processed in the color space includes: for each pixel of the image to be processed, acquiring color pixel values corresponding to three basic colors of pixel data of the pixel in a color space; and converting the color pixel values corresponding to the three basic colors into a luminance characteristic value and a chrominance characteristic value based on a first preset conversion coefficient matrix.
Step S202: and calculating the brightness statistic value of the image to be processed according to the brightness characteristic value of each pixel contained in the image to be processed.
Specifically, the description of calculating the brightness statistic value of the image to be processed is identical to the description of step S102, and will not be repeated here.
Step S203: according to the brightness statistic value, adjusting the brightness characteristic value of each pixel of the image to be processed, and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value; converting the adjusted brightness characteristic value and the adjusted chromaticity characteristic value corresponding to each pixel into adjusted color pixel values corresponding to three basic colors based on a second preset conversion coefficient matrix; and displaying an enhanced image for the image to be processed based on the adjusted color pixel values.
Specifically, regarding the adjustment of the luminance feature value of each pixel of the image to be processed according to the luminance statistic, the description of adjusting the chrominance feature value of the pixel based on the adjusted luminance feature value is consistent with the description of step S103, and will not be repeated here.
Further, correspondingly, after adjusting the characteristic value of the YUV space, converting the color pixel value of the YUV space into an RGB space, and converting the adjusted brightness characteristic value and the adjusted chromaticity characteristic value corresponding to each pixel into adjusted color pixel values corresponding to three basic colors based on a second preset conversion coefficient matrix; displaying an enhanced image for the image to be processed based on the adjusted color pixel values, wherein a conversion expression for converting the color pixel values of the YUV space into the RGB space is as follows:
wherein, For the second preset conversion coefficient matrix, in the embodiment of the present invention, the value of one conversion coefficient is/>
That is, the enhancing the contrast of the image to be processed according to the adjusted luminance feature value and the adjusted chrominance feature value includes: converting the adjusted brightness characteristic value and the adjusted chromaticity characteristic value corresponding to each pixel into adjusted color pixel values corresponding to three basic colors based on a second preset conversion coefficient matrix; and displaying an enhanced image for the image to be processed based on the adjusted color pixel values.
As shown in fig. 4, an embodiment of the present invention provides another process of processing an image, which may include the following steps;
Step S301: and determining pixel characteristics corresponding to each pixel of the image to be processed in a color space, wherein the pixel characteristics comprise a brightness characteristic value and a chromaticity characteristic value.
Specifically, the pixel characteristics corresponding to each pixel of the image to be processed in the color space are determined to be consistent with the description of step S101 or step S201, and will not be described herein.
Step S302: for each pixel of the image to be processed, performing: determining a target brightness segmentation interval to which the brightness characteristic value of the pixel belongs and a statistical parameter corresponding to the target brightness segmentation interval from a plurality of brightness segmentation intervals; and calculating the target brightness value of the pixel according to the brightness characteristic value of the pixel, the statistical parameter corresponding to the target brightness segmentation interval and the first brightness value.
Specifically, the calculation of the target luminance value of the pixel is consistent with the description of step S103, and will not be described herein.
Step S303: and for each pixel of the image to be processed, determining the optimized brightness value of the key pixel by combining the brightness characteristic value of the key pixel and the sharpened brightness value for each key pixel in the image to be processed.
Specifically, the calculation of the optimized luminance value of the key pixel is consistent with the description of step S103, and will not be described herein.
Step S304: according to the brightness statistic value, adjusting the brightness characteristic value of each pixel of the image to be processed, and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value; and enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value.
Specifically, the description of enhancing the contrast of the image to be processed according to the adjusted luminance feature value and the adjusted chrominance feature value is consistent with the description of step S103 or step S203, and will not be described herein.
According to fig. 4, the flow of enhancing the image contrast in one embodiment of the present invention is step S301- > step S302- > step S304; in another embodiment of the present invention, the process of enhancing the contrast of the image is step S301- > step S303- > step S304; preferably, the flow of enhancing the image contrast in still another embodiment of the present invention is step S301- > step S302- > step S303- > step S304.
As shown in fig. 5, an embodiment of the present invention provides an apparatus 400 for processing an image, including: an acquisition feature module 401, a brightness determination module 402, and an adjustment pixel module 403; wherein,
The obtaining feature module 401 is configured to determine a pixel feature corresponding to each pixel of the image to be processed in a color space, where the pixel feature includes a luminance feature value and a chrominance feature value;
The brightness determining module 402 is configured to calculate a brightness statistic value of the image to be processed according to the brightness characteristic value of the image to be processed;
The adjustment pixel module 403 is configured to adjust a luminance feature value of each pixel of the image to be processed according to the luminance statistic, and adjust a chrominance feature value of the pixel based on the adjusted luminance feature value; and enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value.
The embodiment of the invention also provides an electronic device for processing images, which comprises: one or more processors; and a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method provided by any of the embodiments described above.
The embodiment of the invention also provides a computer readable medium, on which a computer program is stored, which when executed by a processor implements the method provided by any of the above embodiments.
The embodiment of the application also provides a chip for realizing any one of the image processing methods. The chip can be a chip for processing the image or a unit for processing the image in the chip, and the method for processing the image provided by the embodiment of the application has the advantages of saving computing resources and high processing accuracy and can be applied to the chip by receiving the image to be processed and outputting the image with enhanced contrast.
The embodiment of the application also provides computer software for realizing any one of the image processing methods. Wherein computer software implementing the method of processing images of the present application can be run in a variety of environments.
Fig. 6 illustrates an exemplary system architecture 500 of a method of processing an image or an apparatus of processing an image to which embodiments of the present invention may be applied.
As shown in fig. 6, the system architecture 500 may include terminal devices 501, 502, 503, a network 504, and a server 505. The network 504 is used as a medium to provide communication links between the terminal devices 501, 502, 503 and the server 505. The network 504 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
A user may interact with the server 505 via the network 504 using the terminal devices 501, 502, 503 to receive or send messages or the like. Various client applications such as an electronic mall client application, a web browser application, a search class application, an instant messaging tool, a mailbox client, and the like may be installed on the terminal devices 501, 502, 503.
The terminal devices 501, 502, 503 may be a variety of electronic devices having a display screen and supporting a variety of client applications, including but not limited to smartphones, tablet computers, laptop and desktop computers, and the like.
The server 505 may be a server providing various services, such as a background management server providing support for client applications used by the user with the terminal devices 501, 502, 503. The background management server can process the received request for contrast enhancement processing of the image and feed the processed image back to the terminal equipment.
It should be noted that, the method for processing an image according to the embodiment of the present invention is generally performed by the server 505, and accordingly, the device for processing an image is generally disposed in the server 505.
It should be understood that the number of terminal devices, networks and servers in fig. 6 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 7, there is illustrated a schematic diagram of a computer system 600 suitable for use in implementing an embodiment of the present invention. The terminal device shown in fig. 7 is only an example, and should not impose any limitation on the functions and the scope of use of the embodiment of the present invention.
As shown in fig. 7, the computer system 600 includes a Central Processing Unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other through a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; an output portion 607 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. The above-described functions defined in the system of the present invention are performed when the computer program is executed by a Central Processing Unit (CPU) 601.
The computer readable medium shown in the present invention may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules and/or units involved in the embodiments of the present invention may be implemented in software, or may be implemented in hardware. The described modules and/or units may also be provided in a processor, e.g., may be described as: a processor includes an acquisition characteristics module, a determination brightness module, and an adjustment pixels module; the names of these modules do not in any way limit the module itself, and the acquisition feature module may also be described as "a module for determining a pixel feature corresponding to each pixel of the image to be processed in the color space", for example.
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be present alone without being fitted into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to include: determining pixel characteristics corresponding to each pixel of an image to be processed in a color space, wherein the pixel characteristics comprise a brightness characteristic value and a chromaticity characteristic value; calculating a brightness statistic value of the image to be processed according to the brightness characteristic value of each pixel contained in the image to be processed; according to the brightness statistic value, adjusting the brightness characteristic value of each pixel of the image to be processed, and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value; and enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value.
According to the embodiment of the invention, the brightness statistic value can be calculated according to the brightness characteristic value of each pixel in the image to be processed; according to the brightness statistic value, adjusting the brightness characteristic value of each pixel, and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value; thereby enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value. The embodiment of the invention improves the definition degree of the contrast of the processed image and improves the processing effect of enhancing the contrast of the image.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives can occur depending upon design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (13)
1. A method of processing an image, comprising:
determining pixel characteristics corresponding to each pixel of an image to be processed in a color space, wherein the pixel characteristics comprise a brightness characteristic value and a chromaticity characteristic value;
Calculating a brightness statistic value of the image to be processed according to the brightness characteristic value of each pixel contained in the image to be processed;
According to the brightness statistic value, adjusting the brightness characteristic value of each pixel of the image to be processed, and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value;
And enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value.
2. The method of claim 1, wherein the step of determining the position of the substrate comprises,
Determining pixel characteristics corresponding to each pixel of the image to be processed in a color space, wherein the pixel characteristics comprise:
for each pixel of the image to be processed, acquiring color pixel values corresponding to three basic colors of pixel data of the pixel in a color space;
and converting the color pixel values corresponding to the three basic colors into a luminance characteristic value and a chrominance characteristic value based on a first preset conversion coefficient matrix.
3. The method of claim 2, wherein the enhancing the contrast of the image to be processed based on the adjusted luminance feature value and the adjusted chrominance feature value comprises:
converting the adjusted brightness characteristic value and the adjusted chromaticity characteristic value corresponding to each pixel into adjusted color pixel values corresponding to three basic colors based on a second preset conversion coefficient matrix;
And displaying an enhanced image for the image to be processed based on the adjusted color pixel values.
4. The method of claim 1, wherein the step of determining the position of the substrate comprises,
The calculating the brightness statistic value of the image to be processed comprises the following steps:
calculating a first brightness statistic value of the image to be processed according to the brightness characteristic value of each pixel in the image to be processed;
Acquiring a second brightness statistic value of an adjacent frame image corresponding to the image to be processed;
calculating a difference between the first luminance statistic and the second luminance statistic;
taking the second brightness statistical value as the brightness statistical value of the image to be processed under the condition that the difference value is lower than a set brightness change threshold value;
And taking the first brightness statistical value as the brightness statistical value of the image to be processed under the condition that the difference value is not lower than a set brightness change threshold value.
5. The method according to claim 1 or 4, wherein,
The adjusting the brightness characteristic value of each pixel of the image to be processed comprises the following steps:
acquiring a minimum brightness value and a maximum brightness value in brightness characteristic values of the image to be processed;
according to the minimum brightness value, the maximum brightness value and the brightness initial statistical value of the image to be processed, calculating a first brightness value of a dark area demarcation point and a second brightness value of a bright area demarcation point of the image to be processed;
Determining a plurality of brightness segmentation intervals of the image to be processed based on the minimum brightness value, the maximum brightness value, the brightness initial statistical value, the first brightness value and the second brightness value, wherein each brightness segmentation interval is correspondingly provided with a statistical parameter;
for each pixel of the image to be processed, performing:
Determining a target brightness segmentation interval to which the brightness characteristic value of the pixel belongs and a statistical parameter corresponding to the target brightness segmentation interval from a plurality of brightness segmentation intervals;
and calculating the target brightness value of the pixel according to the brightness characteristic value of the pixel, the statistical parameter corresponding to the target brightness segmentation interval and the first brightness value.
6. The method according to claim 1 or 5, wherein said adjusting the luminance feature value of each pixel of the image to be processed further comprises:
For each pixel of each row of the image to be processed, executing steps N1-N2:
N1: selecting a set number of pixels in a row where the pixels are located according to a preset direction by taking the pixels as a starting point, forming a pixel group by the set number of pixels, and determining key pixels of the pixel group;
N2: calculating the sharpening brightness value of the key pixel based on the brightness characteristic value of each pixel in the pixel group and a preset position weight;
And determining the optimized brightness value of the key pixel by combining the brightness characteristic value of the key pixel and the sharpened brightness value aiming at each key pixel in the image to be processed.
7. The method of claim 6, wherein said adjusting the luminance feature value of each pixel of the image to be processed further comprises:
In the case where the set number is a plurality of set numbers,
Determining target key pixels which are overlapped in the key pixels corresponding to the set quantity;
and further optimizing the optimized brightness value of the target key pixel based on the optimized brightness value corresponding to the target key pixel obtained by each set quantity and the preset weight corresponding to each set quantity.
8. The method of claim 1, wherein the step of determining the position of the substrate comprises,
The adjusting the chromaticity characteristic value of the pixel based on the adjusted luminance characteristic value includes:
And for each pixel of the image to be processed, determining the chromaticity characteristic value after the pixel adjustment by utilizing the ratio of the brightness characteristic value after the pixel adjustment to the original brightness characteristic value of the pixel and the original chromaticity characteristic value of the pixel.
9. An apparatus for processing an image, comprising: the method comprises the steps of acquiring a characteristic module, determining brightness module and adjusting pixel module; wherein,
The image processing module is used for processing the image to be processed, and acquiring a characteristic module, which is used for determining a pixel characteristic corresponding to each pixel of the image to be processed in a color space, wherein the pixel characteristic comprises a brightness characteristic value and a chromaticity characteristic value;
The brightness determining module is used for calculating the brightness statistic value of the image to be processed according to the brightness characteristic value of the image to be processed;
The pixel adjusting module is used for adjusting the brightness characteristic value of each pixel of the image to be processed according to the brightness statistic value and adjusting the chromaticity characteristic value of the pixel based on the adjusted brightness characteristic value; and enhancing the contrast of the image to be processed according to the adjusted brightness characteristic value and the adjusted chromaticity characteristic value.
10. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
When executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-8.
11. A chip for implementing the method of any one of claims 1-8.
12. Computer software implementing the method of any one of claims 1-8.
13. A computer readable medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311797704.1A CN117911300A (en) | 2023-12-25 | 2023-12-25 | Method and device for processing image |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311797704.1A CN117911300A (en) | 2023-12-25 | 2023-12-25 | Method and device for processing image |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117911300A true CN117911300A (en) | 2024-04-19 |
Family
ID=90688957
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311797704.1A Pending CN117911300A (en) | 2023-12-25 | 2023-12-25 | Method and device for processing image |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117911300A (en) |
-
2023
- 2023-12-25 CN CN202311797704.1A patent/CN117911300A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6615917B2 (en) | Real-time video enhancement method, terminal, and non-transitory computer-readable storage medium | |
| US10783837B2 (en) | Driving method and driving device of display device, and related device | |
| CN108962185B (en) | Method for reducing display image brightness, device thereof and display device | |
| CN103778900B (en) | A kind of image processing method and system | |
| CN101621704B (en) | Method and device for color enhancement for graphic images | |
| WO2019041842A1 (en) | Image processing method and device, storage medium and computer device | |
| CN109309826B (en) | Image color balancing method and device, terminal equipment and readable storage medium | |
| CN110996174B (en) | Video image quality enhancement method and related equipment thereof | |
| WO2006055693A2 (en) | System and method for a vector difference mean filter for noise suppression | |
| CN108600783B (en) | Frame rate adjusting method and device and terminal equipment | |
| US20210185285A1 (en) | Image processing method and apparatus, electronic device, and readable storage medium | |
| CN113935911A (en) | High dynamic range video image processing method, computer device and computer readable storage medium | |
| CN115022679B (en) | Video processing method, device, electronic equipment and medium | |
| CN109272526B (en) | Image processing method and system and electronic equipment | |
| CN110858388B (en) | Method and device for enhancing video image quality | |
| CN110097520B (en) | Image processing method and device | |
| CN111738950B (en) | Image processing method and device | |
| WO2021073316A1 (en) | Image signal conversion method and apparatus, and terminal device | |
| CN109308690B (en) | Image brightness balancing method and terminal | |
| CN117911300A (en) | Method and device for processing image | |
| CN112215237B (en) | Image processing method and device, electronic equipment and computer readable storage medium | |
| CN113762016A (en) | Key frame selection method and device | |
| CN114266803A (en) | Image processing method, image processing device, electronic equipment and storage medium | |
| CN109996017B (en) | Image adjusting method and terminal thereof | |
| TWI720628B (en) | Method and apparatus for enhancing brightness and contrast of video image,storage medium and electronic device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |