WO2020124808A1

WO2020124808A1 - Image enhancement device and image enhancement method

Info

Publication number: WO2020124808A1
Application number: PCT/CN2019/077848
Authority: WO
Inventors: 朱江
Original assignee: 深圳市华星光电半导体显示技术有限公司
Priority date: 2018-12-20
Filing date: 2019-03-12
Publication date: 2020-06-25
Also published as: CN109509161B; CN109509161A

Abstract

Disclosed is an image enhancement device, comprising: computer hardware, a color conversion module, an edge enhancement module, and a saturation compensation module. An image is input to the computer hardware and comprises RGB (red, green, blue) data. The color conversion module converts the RGB data into HSL (hue, saturation, lightness) data, and after the image has been enhanced, the color conversion module can be used to convert HSL data of the enhanced image into RGB data. The edge enhancement module inspects a plurality of pixels in the input image so as to locate a plurality of edge pixels from the plurality of pixels, and performs performance enhancement on the plurality of edge pixels. The saturation compensation module performs compensation on saturation of the edge pixels of the image. The edge enhancement module and the saturation compensation module perform enhancement on edges of the image, and prevent the saturation of the edge pixels of the image from decreasing.

Description

Image enhancement device and image enhancement method

Technical field

The invention relates to an image enhancement device and an image enhancement method, which can simultaneously enhance the edge and color of an image, improve the efficiency of image enhancement, and avoid the problem of dimming the color of the image edge when the prior art only enhances the edge of the image.

Background technique

During the collection, transmission, and conversion of images in a computer or related electronic devices, due to the influence of various factors, the image quality may be reduced, resulting in the phenomenon of blurred edges and pale colors on the image. Therefore, before an image is displayed on a liquid crystal display panel, image enhancement is usually required in advance.

Image enhancement generally includes two types of image edge enhancement and image color enhancement. Image edge enhancement is to process the brightness components of the image edge pixels, so that the image edge is sharper visually and the image is clearer. Image color enhancement is processed for the saturation value of image pixels, making the image color more vivid. In the prior art, the enhancement processes of the image edge enhancement and the image color enhancement are independent of each other. The edge enhancement of the image often causes the brightness of the pixels at the edge of the image to change, while the saturation value and hue value of the pixels do not change. For the image after interpolation and magnification, when the edge of the image is enhanced, the color of the color pixels at the edge will become dark, for example, from bright red to dark red, resulting in a dim color and poor saturation at the edge.

Therefore, it is necessary to provide an image enhancement device and image enhancement method to solve the problems in the prior art.

technical problem

In view of the lack of technical problems in the prior art for simultaneously enhancing the edges and colors of the image, the present invention provides an image enhancement device and image enhancement method to solve the technical problems in the prior art.

Technical solution

The main object of the present invention is to provide an image enhancement device and an image enhancement method, which can simultaneously enhance the edge and color of the image, improve the image enhancement efficiency, and avoid the existing technology that only causes the image edge to be dim when the image edge is enhanced problem.

To achieve the above objective, the image enhancement device of the present invention includes:

Computer hardware for inputting an image into the computer hardware, wherein the image includes red, green and blue data;

A color conversion module, provided in the computer hardware, for converting the red, green, and blue data into hue saturation and brightness data, and for processing the hue of the enhanced image after the image is processed into an enhanced image Saturation brightness data is converted to red, green and blue data;

An edge enhancement module, provided in the computer hardware, for detecting the plurality of pixels in the input image, to find a plurality of edge pixels from the plurality of pixels, and to detect the plurality of edges Pixel enhancement; and

A saturation compensation module, set in the computer hardware, for compensating the saturation of the edge pixels of the image;

After the color conversion module converts the red, green, and blue data of the image into hue saturation brightness data, the edge enhancement module enhances the edge pixels in the image, and the saturation The compensation module compensates the saturation of the edge pixels of the image to form an enhanced image, and finally the color conversion module converts the hue saturation luminance data of the enhanced image into red, green, and blue data.

In an embodiment of the invention, the red-green-blue data includes red, green and blue values for each pixel, and the hue saturation brightness data includes hue values, saturation values and brightness values.

In an embodiment of the present invention, the edge enhancement module is used to perform an edge pixel detection step and an edge pixel performance enhancement step; the edge pixel detection step includes the brightness value according to the hue saturation brightness data, Performing brightness identification on the plurality of pixels in the image to find a plurality of edge pixels from the plurality of pixels; the step of enhancing the edge pixel performance includes adjusting the brightness value of the edge pixel so that The difference in brightness between the edge pixel and the adjacent pixel increases.

In an embodiment of the present invention, the saturation compensation module is used to perform a saturation average calculation step, a saturation difference calculation step, and a saturation adjustment step; the saturation average calculation step includes each of the images Edge pixels as a central pixel, and calculate the average saturation value of adjacent pixels adjacent to the central pixel; the step of calculating the saturation difference value includes calculating the saturation of the central pixel and the average value of the saturation Saturation difference; the saturation adjustment step includes judging whether the saturation difference is greater than 0, if greater than 0, then increasing the saturation of the central pixel, if less than 0, decreasing the saturation of the central pixel P1 To obtain the enhanced image.

In an embodiment of the invention, the saturation average calculation step is based on the following equation: S_av = (S(j-1,i-1) + S(j-1,i) + S(j-1,i+1) + S(j,i-1) + S(j,i+1) + S(j+1,i-1) + S(j+1,i) + S (j+1,i+1))/8; where S_av is the average saturation, S(j-1,i-1), S(j-1,i), S(j-1,i+1 ), S(j,i-1), S(j,i+1), S(j+1,i-1), S(j+1,i), S(j+1,i+1) ) Is the saturation value of the adjacent pixel.

In an embodiment of the present invention, the saturation difference calculation step is based on the following equation: f_s = S(j, i)-S_av; where S(j, i) is the saturation value of the central pixel , F_s is the saturation difference.

In an embodiment of the invention, the computer hardware includes a central processing unit, a memory, a storage, an input interface, and an output interface electrically connected to each other, and the input interface is used to input the image into the computer hardware , The output interface is used to output the enhanced image.

Another object of the present invention is to provide an image enhancement method, including:

Computer provision steps, including provision of computer hardware;

The image input step includes inputting an image to the computer hardware;

The first color data conversion step includes converting the input red, green, and blue data of the image into hue saturation brightness data through the computer hardware;

The edge pixel detection step includes using the computer hardware to perform brightness identification on the plurality of pixels in the image according to the brightness value in the hue saturation brightness data to find from the plurality of pixels Multiple edge pixels;

The step of enhancing the performance of the edge pixel includes adjusting the brightness value of the edge pixel through the computer hardware to increase the difference in brightness between the edge pixel and the adjacent pixel;

A saturation compensation step, including compensating the saturation of edge pixels of the image through the computer hardware; and

The second color conversion step includes using the computer hardware to convert the hue saturation brightness data contained in the enhanced image into red, green, and blue data.

In an embodiment of the invention, the red-green-blue data includes red, green and blue values for each pixel; the hue saturation brightness data includes hue values, saturation values and brightness values.

In an embodiment of the invention, the saturation compensation step includes:

The step of calculating the average value of saturation includes taking each edge pixel of the image as a central pixel and calculating the average value of saturation of adjacent pixels adjacent to the central pixel;

A saturation difference calculation step, including calculating a saturation difference between the saturation of the central pixel and the average of the saturation; and

The saturation adjustment step includes determining whether the saturation difference is greater than 0. If it is greater than 0, the saturation of the central pixel is increased, and if it is less than 0, the saturation of the central pixel P1 is reduced, thereby obtaining the enhancement image.

In an embodiment of the invention, the saturation average calculation step is based on the following equation: S_av = (S(j-1,i-1) + S(j-1,i) + S(j-1,i+1) + S(j,i-1) + S(j,i+1) + S(j+1,i-1) + S(j+1,i) + S (j+1,i+1)) / 8, where S_av is the average saturation, S(j-1,i-1), S(j-1,i), S(j-1,i+1 ), S(j,i-1), S(j,i+1), S(j+1,i-1), S(j+1,i), S(j+1,i+1) ) Is the saturation value of the adjacent pixel.

In an embodiment of the present invention, the saturation difference calculation step is based on the following equation: f_s = S(j, i)-S_av, where S(j, i) is the saturation value of the central pixel , F_s is the saturation difference.

In an embodiment of the invention, the computer hardware includes a central processing unit, a memory, a storage, an input interface, and an output interface electrically connected to each other, and the input interface is used to input the image into the computer hardware And the output interface is used to output the enhanced image.

In an embodiment of the present invention, the image enhancement method further includes an image output step, including outputting the enhanced image to an electronic device through the output interface of the computer hardware.

Beneficial effect

Compared with the prior art, the image enhancement device and the image enhancement method of the present invention include the following advantages:

1. The input image is enhanced by the edge sharpness of the image through the present invention and compensated by saturation, so that the sharpness of the image can be improved while maintaining the saturation of the pixels at the edge of the image to avoid the image being dim.

2. The calculation formula adopted by the present invention is simple and avoids the calculation burden of the computer hardware being too large, so it can avoid increasing the burden of the computer hardware while improving the image quality.

In order to make the above content of the present invention more comprehensible, the preferred embodiments are described below in detail in conjunction with the attached drawings, as follows:

BRIEF DESCRIPTION

FIG. 1 is a block diagram of the hardware and software architecture of the image enhancement device according to the present invention.

FIG. 2 is a schematic diagram of the function execution architecture of the image enhancement device of the present invention.

FIG. 3 is a schematic diagram of the processing flow of the image enhancement device of the present invention.

4 is a schematic diagram of multiple pixels in an image.

5 is a flowchart of steps of the image enhancement method of the present invention.

Embodiments of the invention

Please refer to FIGS. 1 and 2. FIG. 1 is a block diagram of the hardware and software architecture of the image enhancement device according to the present invention. FIG. 2 is a schematic diagram of the function execution architecture of the image enhancement device of the present invention. The image enhancement device of the present invention includes: computer hardware 10, color conversion module 20, edge enhancement module 30, and saturation compensation module 40.

The computer hardware 10 includes a central processing unit 11, a memory 12, a storage 13, an input interface 14 and an output interface 15 that are electrically connected to each other.

The memory 12 may be a random access dynamic memory 12 (Dynamic Random-access Memory, DRAM).

The storage 13 may be a hard disk (Hard Disk) Drive, HDD) or Solid State Drive (SSD).

The input interface 14 can be an electrical connector, such as a universal serial bus (Universal Serial Bus (USB) electrical connector for inputting an image 16 into the computer hardware 10. The image 16 input to the computer hardware 10 includes a plurality of pixels, and includes red, green, blue (Red, Green, Blue, RGB) data, the RGB data 160 includes a red value, a blue value, and a green value for each pixel. The RGB data 160 may be converted into Hue, Saturation, Lightness (HSL) data. The HSL data includes a hue value H, a saturation value S, and a brightness value L. In addition, the image 16 can be stored in the storage 13 after being input into the computer hardware 10 and can be loaded into the memory 12 for processing by the central processor 11.

The output interface 15 may be an electrical connector, such as a high-definition multimedia interface (High Definition Multimedia Interface (HDMI) connector, used to output images to external electronic devices, such as liquid crystal display panels.

Please refer to FIG. 3, which is a schematic diagram of the processing flow of the image enhancement device of the present invention. In detail, the computer hardware 10 itself may perform the image input step S02, including inputting an image 160 to the computer hardware 10.

The color conversion module 20 is provided in the computer hardware 10 and can be stored in the storage 13 for software to convert RGB data 160 into HSL data and to convert HSL data into RGB data 160. The color conversion module 20 can convert the input RGB data 160 of the image 16 into HSL data. In detail, the color conversion module 20 may perform a first color data conversion step S03, including converting the input RGB data 160 of the image 16 into HSL data.

The edge enhancement module 30 is provided in the computer hardware 10, and may be stored in the storage 13 for software to detect the plurality of pixels in the input image 16 so as to Find a plurality of edge pixels among the plurality of pixels, and perform performance enhancement on the plurality of edge pixels. The edge pixels mentioned here are the pixels on the inner or outer contour of people, objects, and scenes in the image under normal conditions. For example, the pixels on the contour of the boundary between the face and the background in the image are the edges. Pixels. In addition, in detail, the edge enhancement module 30 may perform the following steps: an edge pixel detection step S04 and an edge pixel performance enhancement step S05.

The edge pixel detection step S04 includes performing brightness identification on the plurality of pixels in the image 16 according to the brightness value L in the HSL data to find a plurality of edge pixels from the plurality of pixels .

The edge pixel performance enhancement step S05 includes adjusting the brightness value L of the edge pixel to increase the brightness difference between the edge pixel and the adjacent pixel. Generally speaking, the adjustment of the brightness value L includes reducing the brightness of the edge pixel to increase the brightness difference between the edge pixel and the adjacent pixel, thereby providing the outline of the people, objects, and scenes included in the image 16 Sharpness. Through the edge pixel performance enhancement step S05, the brightness difference between the edge pixel and the neighboring pixel can be enlarged, thereby increasing the sharpness of people, objects, and scenes in the image 16.

The saturation compensation module 40 is provided in the computer hardware 10 and may be stored in the storage 13 for software to compensate for the saturation of edge pixels of the image 16. In detail, the saturation compensation module 40 may perform a saturation compensation step S06, including compensating the saturation of the edge pixels of the image 16. In detail, the saturation compensation step S06 includes: a saturation average calculation step S06A, a saturation difference calculation step S06B, and a saturation adjustment step S06C.

Please refer to FIG. 4, which is a schematic diagram of a plurality of pixels in the image 16. The saturation average calculation step S06A includes taking each edge pixel of the image 16 as a central pixel P1 (its coordinates are (j, i)), and calculating adjacent pixels adjacent to the central pixel P1 The average saturation value of P2 is S_av. For example, among the 9 pixels in the 3 x 3 matrix shown in FIG. 4, the pixel at the center is the edge pixel and also the center pixel P1, and the remaining 8 pixels are adjacent pixels P2. The detailed calculation method is shown in the following equation 1:

Equation 1: S_av = ( S(j-1,i-1) + S(j-1,i) + S(j-1,i+1) + S(j,i-1) + S(j,i+1) + S (j+1,i-1) + S(j+1,i) + S(j+1,i+1)) / 8.

The saturation difference calculation step S06B includes calculating the saturation difference f_s between the saturation S(j,i) of the central pixel and the saturation average S_av. The detailed calculation method is shown in the following equation 2:

Equation 2: f_s = S(j, i)- S_av.

It can be known from the above-mentioned saturation difference calculation step S06B that the amount by which the saturation S(j, i) of the central pixel P1 is increased or decreased is proportional to f_s.

The saturation adjustment step S06C includes determining whether the saturation difference value f_s is greater than 0, if f_s>0, then increasing the saturation S(j,i) of the central pixel P1, if f_s<0, reducing the The saturation S(j,i) of the central pixel P1 further obtains an enhanced image 16a, as shown in FIG.

The computer hardware 10 then converts the HSL data contained in the enhanced image 16a into RGB data 160. In detail, the computer hardware may perform a second color conversion step S07, including converting the HSL data contained in the enhanced image 16a into RGB data 160.

Finally, the computer hardware 10 outputs the enhanced image 16a to the electronic device 50 through the output interface 15, for example, to a liquid crystal display panel, then the image presented by the electronic device 50 is enhanced and has appropriate sharpness Degree and saturation image 16a. In detail, the computer hardware 10 may perform an image output step S08, including the enhanced image 16a being output to the electronic device 50 through the output interface 15 of the computer hardware 10.

Please refer to FIG. 4 and FIG. 5, which is a flowchart of steps of the image enhancement method of the present invention. The image enhancement method includes: a computer providing step S01, an image input step S02, a first color data conversion step S03, an edge pixel detection step S04, an edge pixel performance enhancement step S05, a saturation compensation step S06, a second color conversion step S07 And the image output step S08.

The computer providing step S01 includes providing a computer hardware 10 as shown in FIG. 1.

The image input step S02 includes inputting an image 160 to the computer hardware 10.

The first color data conversion step S03 includes using the computer hardware 10 to convert the input RGB data 160 of the image 16 into HSL data.

The edge pixel detection step S04 includes, through the computer hardware 10, performing brightness recognition on the plurality of pixels in the image 16 according to the brightness value L in the HSL data, so as to select from the plurality of pixels Find multiple edge pixels.

The edge pixel performance enhancement step S05 includes adjusting the brightness value L of the edge pixel by the computer hardware 10, so that the brightness difference between the edge pixel and the adjacent pixel is increased.

The saturation compensation step S06 includes compensating the saturation of the edge pixels of the image 16 through the computer hardware 10. In detail, the saturation compensation step S06 includes the above-mentioned saturation average calculation step S06A, saturation difference calculation step S06B, and saturation adjustment step S06C.

The second color conversion step S07 includes using the computer hardware 10 to convert the HSL data contained in the enhanced image 16a into RGB data 160.

The image output step S08 includes outputting the enhanced image 16 a to the electronic device 50 through the output interface 15 of the computer hardware 10 through the computer hardware 10.

Claims

An image enhancement device, including:

Computer hardware for an image input into the computer hardware, wherein the image includes red, green and blue data;

A color conversion module, provided in the computer hardware, for converting the red, green, and blue data into hue saturation and brightness data, and for processing the hue of the enhanced image after the image is processed into an enhanced image Saturation brightness data is converted to red, green and blue data;

An edge enhancement module, provided in the computer hardware, for detecting the plurality of pixels in the input image, to find a plurality of edge pixels from the plurality of pixels, and to detect the plurality of edges Pixel performance enhancement; and

A saturation compensation module, set in the computer hardware, for compensating the saturation of the edge pixels of the image;

After the color conversion module converts the red, green, and blue data of the image into hue saturation luminance data, the edge enhancement module enhances the performance of the edge pixels in the image, and the saturation The degree compensation module compensates the saturation of the edge pixels of the image to form an enhanced image, and finally the color conversion module converts the hue saturation brightness data of the enhanced image into red, green, and blue data.
The image enhancement device according to claim 1, wherein the red-green-blue data includes a red value, a green value, and a blue value for each pixel, and the hue saturation brightness data includes a hue value, a saturation value And the brightness value.
The image enhancement device according to claim 2, wherein the edge enhancement module is used to perform an edge pixel detection step and an edge pixel performance enhancement step; the edge pixel detection step includes all data in the hue saturation luminance data The brightness value, performing brightness identification on the plurality of pixels in the image to find a plurality of edge pixels from the plurality of pixels, and the step of enhancing edge pixel performance includes performing brightness values on the edge pixels To adjust the brightness difference between the edge pixel and the adjacent pixel.
The image enhancement device according to claim 2, wherein the saturation compensation module is configured to perform a saturation average calculation step, a saturation difference calculation step, and a saturation adjustment step, the saturation average calculation step includes Each edge pixel of the image serves as a central pixel, and calculates the average saturation value of adjacent pixels adjacent to the central pixel, and the step of calculating the saturation difference includes calculating the saturation of the central pixel and the The saturation difference of the average saturation, and the saturation adjustment step includes determining whether the saturation difference is greater than 0, if greater than 0, increasing the saturation of the central pixel, if less than 0, decreasing the central The saturation of the pixel P1 to obtain the enhanced image.
The image enhancement device according to claim 4, wherein the saturation average calculation step is based on the following equation: S_av = ( S(j-1,i-1) + S(j-1,i) + S(j-1,i+1) + S(j,i-1) + S(j,i+1) + S (j+1,i-1) + S(j+1,i) + S(j+1,i+1)) / 8, where S_av is the average saturation, S(j-1,i-1), S(j-1,i) , S(j-1,i+1), S(j,i-1), S(j,i+1), S(j+1,i-1), S(j+1,i), S(j+1,i+1)) is the saturation value of the adjacent pixels.
The image enhancement device according to claim 4, wherein the saturation difference calculation step is based on the following equation: f_s = S(j, i)-S_av, where S(j, i) is the central pixel The saturation value, f_s is the saturation difference.
The image enhancement device according to claim 1, wherein the computer hardware includes a central processing unit, a memory, a memory, an input interface, and an output interface electrically connected to each other, the input interface is used to input the image to all In the computer hardware, and the output interface is used to output the enhanced image.
An image enhancement method, including:

Computer provision steps, including provision of computer hardware;

The image input step includes inputting an image to the computer hardware;

The first color data conversion step includes converting the input red, green, and blue data of the image into hue saturation brightness data through the computer hardware;

The edge pixel detection step includes using the computer hardware to perform brightness identification on the plurality of pixels in the image according to the brightness value in the hue saturation brightness data to find from the plurality of pixels Multiple edge pixels;

The step of enhancing the performance of the edge pixel includes adjusting the brightness value of the edge pixel through the computer hardware to increase the difference in brightness between the edge pixel and the adjacent pixel;

A saturation compensation step, including compensating the saturation of edge pixels of the image through the computer hardware; and

The second color conversion step includes using the computer hardware to convert the hue saturation brightness data contained in the enhanced image into red, green, and blue data.
The image enhancement method according to claim 8, wherein the red-green-blue data includes a red value, a green value, and a blue value for each pixel, and the hue saturation brightness data includes a hue value, a saturation value And the brightness value.
The image enhancement method according to claim 9, wherein:

The saturation compensation step includes:

The step of calculating the average value of saturation includes taking each edge pixel of the image as a central pixel and calculating the average value of saturation of adjacent pixels adjacent to the central pixel;

A saturation difference calculation step, including calculating a saturation difference between the saturation of the central pixel and the average of the saturation; and

The saturation adjustment step includes determining whether the saturation difference is greater than 0. If it is greater than 0, the saturation of the central pixel is increased, and if it is less than 0, the saturation of the central pixel P1 is reduced, thereby obtaining the enhancement image.
The image enhancement method according to claim 10, wherein the saturation average calculation step is based on the following equation: S_av = (S(j-1,i-1) + S(j-1,i) + S(j-1,i+1) + S(j,i-1) + S(j,i+1) + S(j+1,i-1) + S(j+1,i) + S (j+1,i+1)) 8, where S_av is the average saturation, S(j-1,i-1), S(j-1,i), S(j-1,i+1 ), S(j,i-1), S(j,i+1), S(j+1,i-1), S(j+1,i), S(j+1,i+1) ) Is the saturation value of the adjacent pixel.
The image enhancement method of claim 10, wherein the saturation difference calculation step is based on the following equation: f_s = S(j, i) -S_av, where S(j, i) is the saturation value of the central pixel, and f_s is the saturation difference value.
The image enhancement method according to claim 8, wherein the computer hardware includes a central processing unit, a memory, a memory, an input interface, and an output interface electrically connected to each other, and the input interface is used to input the image to all In the computer hardware, and the output interface is used to output the enhanced image.
The image enhancement method according to claim 8, wherein the image enhancement method further includes an image output step including outputting the enhanced image to an electronic device through the output interface of the computer hardware.