TWM448754U - Image contrast enhancement system - Google Patents

Description

Image contrast enhancement system

The present invention relates to an image correction system, and more particularly to an image contrast enhancement system.

Significant image contrast and perception are the basis for determining image attributes. In daily life, we often capture images in different scenes, and can be divided into five types according to their image contrast distribution: dark image, bright image, back-lighted image. Low contrast images and high contrast images, where overly dark images, overly bright images, backlit images, and low contrast images are considered to be poor quality images. That is to say, these types of images are unacceptable in the human visual system, and the main cause of poor image quality is mostly caused by insufficient or excessive light source in the shooting environment.

At present, it is common practice to capture and analyze the brightness of the image for the adjustment of the brightness of the image. However, the adjustment of the brightness of the overall image does not really improve the shortcomings of the contrast between the details of the image. In the process of improving the contrast distribution of images, it is easy to cause unnatural phenomena such as image unevenness distortion, block effect, chromatic aberration and detail distortion, and the image quality is worse.

Therefore, one aspect of the present invention is to provide an image contrast enhancement system that produces an adaptability by correcting the brightness value of the image itself. The power function is used to correct the visibility of the image. Thereby, the brightness can be corrected according to the brightness problem of different images, thereby effectively improving the image quality.

According to an embodiment of the present invention, an image contrast enhancement system is provided, which is coupled to a camera device and includes an input module, a brightness analysis module, a brightness correction module, and an output module. The input module obtains an input image from the camera. The brightness analysis module is connected to the input module for extracting an original brightness data r from the input image, and the original brightness data includes a plurality of gray level values, wherein the brightness analysis module includes a region dividing unit for using the gray level value Divided into M columns, and takes N columns from the gray scale values of the original luminance data to form a matrix of luminance regions, where N is a complex number and is an odd number. The brightness correction module is coupled to the brightness analysis module for generating an adaptive brightness data to correct an input image from the original brightness data to generate an output image, wherein the brightness correction module includes an average value calculation unit, a parameter setting unit, and A function execution unit. The average calculation unit is configured to respectively calculate an average value mean ( r _N ) according to the gray scale value of the luminance region matrix, where N represents the number of columns of the luminance region matrix, and r _N represents the luminance region matrix. The parameter setting unit is connected to the average value calculating unit for setting an adaptive power parameter γ , wherein when mean ( r _N )< r _A , And when mean ( r _N )> r _A , γ = 3.5 × mean ( r _N ), r _A is the middle value of one of the gray scale value ranges in the original luminance data. The function execution unit is connected to the parameter setting unit for sequentially setting an adaptive power function S from the first column gray scale value to the first M column gray scale value of the original luminance data to correct the brightness region matrix. Column grayscale values to produce an adaptive luminance data, where S = ( r _L ) ^γ , L represents the matrix of the luminance region matrix Column grayscale value. The output module is connected to the brightness correction module for outputting an output image.

According to the image contrast enhancement system described above, the brightness analysis module further includes an image conversion unit connected to the area dividing unit for converting the three primary color data formats (RGB) of the input image into a color space data format having a clearness component. The color space data format with the apparent component is HSI, HSV or YCrCb. In the image contrast enhancement system, the brightness correction module may further comprise a data replacement unit coupled to the function execution unit for replacing the original brightness data with the adaptive brightness data to generate an output image. Furthermore, the aforementioned gray scale value may be set between 0 and 1, and the average value r _{A of the} aforementioned gray scale values may be 0.5. In addition, the function execution unit may use the adaptive power function S to sequentially correct from a first column grayscale value to an Mth column grayscale value to generate adaptive luminance data, and the luminance region matrix system utilized. Take the grayscale values of each column as the reference to the sides of each column Column, plus each column itself, becomes a matrix of luminance regions of N columns, where one side is not sufficient When the column is listed, the number of insufficient columns is complemented by the other side to produce adaptive brightness data.

Thereby, the image contrast enhancement system of the above embodiment can be corrected according to the brightness contrast problem existing in the input image itself, and the image is highlighted. Section, produces a clear output image and avoids the phenomenon of distortion, more in line with the perception of human vision.

Please refer to FIG. 1 , which is a schematic diagram of an image contrast enhancement system according to an embodiment of the present invention. The image contrast enhancement system 200 is connected to an imaging device 100, so that the imaging device 100 can immediately correct the image after the image is captured, thereby optimizing the image contrast. Of course, the image contrast enhancement system 200 of the present invention can also be stored in a computer readable recording medium, so that the computer can read the recording medium and perform an image contrast enhancement processing system. Computer-readable recording media can be read-only memory, flash memory, floppy disk, hard disk, optical disk, flash drive, tape, network accessible database or familiar with the art can easily think of the same The function of the computer can read the recording medium.

As can be seen from FIG. 1 , the image contrast enhancement system 200 includes an input module 210 , a brightness analysis module 220 , a brightness correction module 230 , and an output module 240 . The input module 210 acquires an input image from the imaging device 100. The brightness analysis module 220 is connected to the input module 210. The brightness correction module 230 is connected to the brightness analysis module 220 for receiving the input image and performing analysis and correction to generate an output image. The output module 240 is connected to the brightness correction module 230 for outputting an output image.

In detail, the brightness analysis module 220 is configured to extract the original brightness data r from the input image, wherein the original brightness data includes a plurality of gray level values, and the gray level value is set between 0 and 1, wherein 0 represents black (ie, Dark), 1 means white (ie bright). The brightness analysis module 220 includes an image conversion unit 221 and an area dividing unit 222. The image conversion unit 221 is connected to the area dividing unit 222 for converting the three primary color data formats (RGB) of the input image into a color space data format having a clear visual component, wherein the color spatial data format having the clear visual component is HSI, HSV or YCrCb. The area dividing unit 222 is configured to divide the grayscale value into M columns, and take N columns from the grayscale values of the original luminance data to form a matrix of luminance regions, where N is a complex number and is an odd number. Since the external light source when shooting an image is usually distributed from top to bottom or from bottom to top (or left to right or right to left), the gray scale of the image is transmitted in units of columns (or rows). Value partitioning, this partitioning method can conform to the brightness distribution of the image itself to accurately correct the brightness requirements of different areas.

The brightness correction module 230 is configured to generate an adaptive brightness data correction original image from the original brightness data r to generate an output image. The brightness correction module 230 includes an average value calculation unit 231, a parameter setting unit 232, a function execution unit 233, and a data replacement unit 234. The average value calculating unit 231 is configured to respectively calculate an average value mean ( r _N ) according to the gray scale values of the luminance region matrix, where N represents the number of columns of the luminance region matrix, and r _N represents the luminance region matrix. By calculating the average value of the gray scale values of each column, the distribution of the brightness of each column can be clearly obtained. The parameter setting unit 232 is connected to the average value calculating unit for setting an adaptive power parameter γ , wherein when mean ( r _N )< r _A , And when mean ( r _N )> r _A , γ = 3.5 × mean ( r _N ), r _A is the middle value of one of the gray scale value ranges in the original luminance data. Since the range of the gray scale value is set between 0 and 1, it is also possible to directly set r _A to 0.5, that is, the middle value of the gray scale value range, so that the brightness correction has a more objective standard. The function execution unit 233 is connected to the parameter setting unit for sequentially setting an adaptive power function S from the first column gray scale value to the first M column gray scale value of the original luminance data to correct the brightness region matrix. Column grayscale values to produce an adaptive luminance data, where S = ( r _L ) ^γ , L represents the matrix of the luminance region matrix Column grayscale value. Thereby, the adaptive power function S applicable to each column is defined according to the average gray scale value of each column, which can be closer to the correction requirement of each column. Furthermore, the brightness analysis and the adaptive power parameter are set by column partitioning and corrected by the adaptive power function, which helps to adjust the brightness of the image, enhance the contrast of the image, and improve the light source when shooting the image. Excessive brightness of the light source. The data replacement unit 234 is coupled to the function execution unit for replacing the original luminance data with the adaptive luminance data to generate an output image.

Further, the function execution unit 233 can further correct the first column grayscale value to the Mth column grayscale value by using the adaptive power function S to generate adaptive luminance data. Alternatively, the function execution unit 233 may use the luminance region matrix system to respectively take the two sides of each column on the basis of the gray scale values of the columns. Column, plus each column itself, becomes a matrix of luminance regions of N columns, where one side is not sufficient When the column is listed, the number of insufficient columns is complemented by the other side to produce adaptive brightness data.

When the number of columns in which the gray scale value is divided is larger (that is, the value of N is larger), the finer the partition representing the gray scale value, the finer the input image can be corrected, and the degree of image contrast is relatively improved.

By correcting the brightness problem according to the gray scale values of each column, the details of the image can be effectively highlighted, a clear output image is generated and distortion is avoided, and the perception of human vision is more suitable.

Please refer to Annex 1, where (a) is the original image, and (b) is the original image corrected by Power Function, but the correction is the overall correction, but the original image is not divided into rows or columns for correction. . (c) The output image produced by dividing the original image into 17 lines and correcting it by the above-described image contrast enhancement system. (d) The output image produced by dividing the original image into 33 lines and correcting it by the above-described image contrast enhancement system.

As can be seen from Annex 1, images compared to (c) and (d), (b) do not significantly improve the backlight, over-bright or too dark images. In the correction process, the original image is divided into 33 lines of corrected results (d), and the original image is divided into 17 lines of corrected results (c) more detailed, more prominent image details, and images It is clearer and has no distortion, which is more in line with the perception of human vision.

Referring again to Annex 2 to Annex 6, the image contrast enhancement system of the present invention is used as a computer program and executed on a computer. Attachment 2 is the screen that the computer program opens. Attachment 3 is to load an input image (Original Image), and the right side of the image will display the Histogram of Image of the input image (Original Image), where the X axis is the brightness value and the Y axis is the number of pixels. And in the type field, the user can choose to input the image. Like partitioning in a row or partitioning in a row. As can be seen from Annex 4, the user can select the number of lines to be divided, including 9, 17, 25, 33, 41 for the user to select according to requirements. Of course, the more rows you select, the higher the detail of the image correction. Continuing with reference to Annex 5, the user selects the Row partition and divides the input image into 9 columns to obtain the left-side corrected output image (9 Row-base by Power Function), and further obtains the output image. Histogram of Row-base, where the X-axis is the luminance value and the Y-axis is the number of pixels.

In addition, in the attachment 6, the user selects the column partition and divides the input image into 17 columns, and the left corrected image (17Column-base by Power Function) can be obtained, and the output image can be further obtained. Histogram of Column-base, where the X-axis is the luminance value and the Y-axis is the number of pixels.

Although the present invention has been disclosed in the above embodiments, it is not intended to limit the present invention. Any one skilled in the art can make various changes and retouchings without departing from the spirit and scope of the present invention. The scope is subject to the definition of the scope of the patent application attached.

100‧‧‧ camera

200‧‧‧Image contrast enhancement system

210‧‧‧Input module

220‧‧‧Brightness Analysis Module

221‧‧‧Image Conversion Unit

222‧‧‧Divisional unit

230‧‧‧Brightness correction module

231‧‧‧Average calculation unit

232‧‧‧ parameter setting unit

233‧‧‧ function execution unit

234‧‧‧data replacement unit

240‧‧‧Output module

The above and other objects, features, advantages and embodiments of the present invention will become more apparent and understood.

FIG. 1 is a schematic diagram of an image contrast enhancement system according to an embodiment of the present invention.

100‧‧‧ camera

200‧‧‧Image contrast enhancement system

210‧‧‧Input module

220‧‧‧Brightness Analysis Module

221‧‧‧Image Conversion Unit

222‧‧‧Divisional unit

230‧‧‧Brightness correction module

231‧‧‧Average calculation unit

232‧‧‧ parameter setting unit

233‧‧‧ function execution unit

234‧‧‧data replacement unit

240‧‧‧Output module

Claims (8)

An image contrast enhancement system is connected to a camera device. The image contrast enhancement system includes: an input module for acquiring an input image from the camera device; and a brightness analysis module coupled to the input module for An original luminance data r is obtained from the input image, the original luminance data includes a plurality of grayscale values, wherein the luminance analysis module includes: a region dividing unit, configured to divide the grayscale values into M columns, and Taking N columns from the grayscale values of the original luminance data to form a matrix of luminance regions, where N is a complex number and an odd number; a luminance correction module is coupled to the luminance analysis module for the original luminance The data r generates an adaptive brightness data to correct the input image to generate an output image, wherein the brightness correction module includes: an average value calculating unit configured to calculate one grayscale value according to the brightness region matrix average mean (r _N), where N is the number of columns in the matrix area of the brightness, the brightness _N represents R & lt matrix region; a parameter setting unit, connected to the average calculation unit For setting an adaptive parameter gamma] exponentiation, wherein when the mean (r _N) <r _A, the And when mean ( r _N )> r _A , γ = 3.5 × mean ( r _N ), r _{A is} an intermediate value of one of the gray scale value ranges in the original luminance data; and a function execution unit, and the The parameter setting unit is connected to sequentially set an adaptive power function S from the first column grayscale value to the first M column grayscale value of the original luminance data to correct the brightness region matrix. Column grayscale values to produce an adaptive luminance data, where S = ( r _L ) ^γ , L represents the matrix of the luminance region matrix a gray scale value; and an output module coupled to the brightness correction module for outputting the output image. The image contrast enhancement system of claim 1, wherein the brightness analysis module comprises: an image conversion unit coupled to the area dividing unit for converting the three primary color data formats (RGB) of the input image to have a clear view The color space data format of the degree component. The image contrast enhancement system of claim 2, wherein the color space data format having the visibility component is HSI, HSV or YCrCb. The image contrast enhancement system of claim 1, wherein the brightness correction module comprises: a data replacement unit coupled to the function execution unit for replacing the original brightness data with the adaptive brightness data to generate the output image . The image contrast enhancement system of claim 1, wherein the grayscale values are set between 0 and 1. The image contrast enhancement system of claim 1, wherein the average value r _A of the gray scale values is 0.5. The image contrast enhancement system of claim 1, wherein the function execution unit uses the adaptive power function S to sequentially correct from a first column grayscale value to an Mth column grayscale value to generate the adaptation. Sexual brightness data. The image contrast enhancement system of claim 1, wherein the function execution unit uses the luminance region matrix to respectively take each side of the column with the grayscale value of the column. a column, plus each of the columns themselves, becomes the matrix of the luminance regions of the N columns, wherein one of the sides is insufficient When the column is listed, the number of insufficient columns is complemented by the other side to generate the adaptive brightness data.