WO2013185449A1

WO2013185449A1 - Image enhancement method, image enhancement device and display device

Info

Publication number: WO2013185449A1
Application number: PCT/CN2012/085983
Authority: WO
Inventors: 张晓�; 冯朋朋; 张一凡
Original assignee: 京东方科技集团股份有限公司; 北京京东方显示技术有限公司
Priority date: 2012-06-13
Filing date: 2012-12-05
Publication date: 2013-12-19
Also published as: CN102779330A; CN102779330B

Abstract

An image enhancement method, an image enhancement device and a display device are provided. The method comprises the following steps: transforming an original image from the RGB color space into the HSI color space (101); keeping the hue component unchanged, respectively performing the enhancement processing of the luminance component and saturation component to obtain a processed image (102); and transforming the processed image from the HSI color space into the RGB color space (103). The present invention transforms the image from the RGB color space into the HSI color space to perform enhancement processing, thus the defect of color loss can be avoided.

Description

Image enhancement method, image enhancement device and display device

Embodiments of the present invention relate to the field of image processing, and in particular, to an image enhancement method, an image enhancement device, and a display device. Background technique

During the acquisition process, the image may be affected by factors such as the dynamic range of the imaging device and the intensity of the ambient light, resulting in low contrast, inconspicuous image information, color distortion, insufficient outline of the target or insufficient clarity of the boundary information. The phenomenon brings difficulties to human visual observation and machine analysis processing, and thus it is necessary to enhance the image.

Image enhancement refers to the processing of highlighting certain information of an image according to specific needs, while weakening or removing some unwanted information. It is the most basic means of image processing. It is often a preprocessing process for various image analysis and processing. .

Currently, images are usually enhanced directly in the RGB color space, which is prone to color loss defects. Summary of the invention

In view of this, embodiments of the present invention provide an image enhancement method, an image enhancement apparatus, and a display apparatus, which can perform an enhancement process by converting an image from an RGB color image to an HSI color space, thereby avoiding the defect of color loss.

To solve the above problem, an embodiment of the present invention provides an image enhancement method, including: converting an original image from a red, green, and blue RGB color space to a hue, saturation, and brightness HSI color space;

Keeping the hue component unchanged, and separately enhancing the luminance component and the saturation component to obtain the processed image;

The processed image is converted from the HSI color space to the RGB color space.

Preferably, the step of performing enhancement processing on the luminance component comprises:

Locally enhancing the luminance component of the original image by using a Retinex visual model to obtain a locally enhanced image;

The global brightness adjustment is performed on the locally enhanced image using a gamma transform. Preferably, before the step of performing local enhancement processing on the luminance component by using a Retinex visual model, the method further includes:

The gray level of the luminance component is normalized to obtain a normalized luminance component as a luminance component of the original image.

Preferably, the luminance component of the original image is locally enhanced by the following formula: t(x, y) = I(x, y) * G(x, y)

Where J'(x, _y) is the ambient brightness function after local enhancement processing, /(x, _y) is the luminance component of the original image, G(x, _y) is the Gaussian function, and the calculation of G(x, _y) The formula is:

^G ( ^x ' ⁼ , σ is the standard deviation of the Gaussian function;

进行 Global brightness adjustment of the locally enhanced image using the following formula:

Where , is the ambient brightness function after the global brightness adjustment, and γ is the gamma transform coefficient. Preferably, the saturation component is enhanced by the following formula:

Wherein, to enhance the processed saturation component, S is a saturation component of the original image,

R'(x, _y) is the reflected light information of the object after global brightness adjustment. The calculation formula of R'(x, _y) is:

K(x,y)= ^(x , + , Γ is the average brightness of the reflected light information of the object, depending on the number of bits of the original image, /(x, _y) is the luminance component of the original image, J; (x The image brightness enhancement device is provided for the global brightness adjustment. The embodiment of the invention further provides an image enhancement device, including:

a first conversion module, configured to convert an original image from a red, green, and blue RGB color space to a hue, saturation, and brightness HSI color space;

An image enhancement module, configured to maintain a hue component unchanged, and perform enhancement processing on the luma component and the saturation component respectively to obtain a processed image;

And a second conversion module, configured to convert the processed image from an HSI color space to an RGB color space. Preferably, the image enhancement module comprises:

a local enhancement module, configured to perform local enhancement processing on a luminance component of the original image by using a Retinex visual model to obtain a locally enhanced image;

And a global enhancement module, configured to perform global brightness adjustment on the locally enhanced image by using a Gamma transform.

Preferably, the image enhancement module further includes:

a normalization processing module, configured to normalize a gray level of a luminance component of the original image, to obtain a normalized luminance component, and use the normalized luminance component as the original image The luminance component is sent to the local enhancement module.

Preferably, the image enhancement module further includes:

And a saturation enhancement module, configured to perform enhancement processing on the saturation component according to the relationship between the saturation component and the luminance component.

The embodiment of the invention further provides a display device comprising the above image enhancement device.

Embodiments of the present invention have the following beneficial effects:

Converting images from RGB color space to HSI color space for image enhancement processing can avoid image loss processing directly in the RGB color space and cause color loss defects. In addition, images processed in HSI color space are processed in RGB color space. The image is more suitable for human visual characteristics. DRAWINGS

1 is a schematic flow chart of an image enhancement method according to an embodiment of the present invention;

2 is another schematic flowchart of an image enhancement method according to an embodiment of the present invention;

FIG. 3 is still another schematic flowchart of an image enhancement method according to an embodiment of the present invention; FIG.

FIG. 4 is a schematic structural diagram of an image enhancement apparatus according to an embodiment of the present invention. detailed description

The specific embodiments of the present invention are further described in detail below with reference to the drawings and embodiments. FIG. 1 is a schematic flowchart diagram of an image enhancement method according to an embodiment of the present invention, where the image enhancement method includes the following steps:

Step 101: Convert the original image from the red, green, and blue RGB color spaces to the hue and saturation Degree, brightness HSI color space;

Step 102: Keep the tone component unchanged, and perform enhancement processing on the luminance component and the saturation component respectively to obtain the processed image.

Among them, keeping the hue component unchanged, it can be guaranteed that the processed image has no color shift. Step 103: Convert the processed image from an HSI color space to an RGB color space. Existing display devices use the RGB color space, and finally the enhanced processed image needs to be converted from the HSI color space to the RGB color space.

In the above embodiment, since the image is enhanced by converting the image from the RGB color space to the HSI color space, it is possible to avoid the defect of color loss directly by performing image enhancement processing in the RGB color space, and further, the image processed in the HSI color space. It is more suitable for human visual characteristics than images processed in the RGB color space.

The specific implementation process of each step in the above embodiment will be described in detail below with reference to FIGS. 2 and 3.

(1) color space conversion

In one example, in the above step 101, the original image may be converted from the RGB color space to the HSI color space using the following conversion formula: H=

= l-i ~~ - ~~ ^"min (R,G,B)1;

(R + G + B) ^L , , , ,"'

I=-(R + G + B); where H, S, and I are the hue component, the saturation component, and the luminance component, respectively, and R, G, and B are the red, green, and blue components of the original image, respectively.

Of course, in the above step 101, it is not excluded to convert the original image from the RGB color space to the HSI color space by using other conversion formulas.

After the color space conversion, the luminance component /(x,_y) of the original image, the hue component H(x,_y), and the saturation component S(x, , where (x, _y) represent the coordinates of the pixel are obtained.

(2) Enhancement processing of luminance component and saturation component (2.1) Referring to FIG. 2, in an example, in the above step 102, the luminance component /(X, y) may be enhanced by the following steps:

(2.11) Using the Retinex visual model to locally enhance the luminance component of the original image to obtain a locally enhanced image;

As can be seen from the definition of the Retinex visual model, the luminance component of an image can be represented by the product of the ambient luminance function and the object's reflected illumination information:

I(x,y) = R(x,y)L(x,y)

Where R(x, _y) is the reflected light information of the object, and (x, _y) is the ambient brightness function.

In the local enhancement process, the ambient brightness function is processed. Specifically, the center component can be used to convolve the luminance component of the original image with the Gaussian function to obtain the local brightness enhancement process ^ , : t (x,y)=I(x,y)*G(x,y) ,

^G ( ^x ' ⁼ , σ is the standard deviation of the Gaussian function;

(2.12) The global brightness adjustment is performed on the locally enhanced image by the Gamma transform, that is, the global enhancement processing.

The global brightness adjustment can be performed on the image after local enhancement processing using the following formula:

Among them, (χ, is the ambient brightness function after global brightness adjustment, which is the Gamma transform coefficient. As the image increases, the brightness component of the image also increases. Because the human eye is more sensitive to medium-brightness image details, It is less sensitive to low-brightness and high-brightness image details, so different values should be used for different brightness images.

For example, the brightness interval of an 8-bit image is divided into three brightness intervals: low, medium, and high. The brightness range of each interval is [0, 39], [40, 179], [180, 255]. After experimental analysis, γ can use the following values:

0635 i/0≤I(x,y)≤39

γ = \ 0414 i/40 ≤ I(x, y) ≤ 179

0523 i/180≤I(x,y)≤255 Of course, in other embodiments of the present invention, other brightness enhancement methods may be used to enhance the luminance component, which is not described here.

(2.2) In the above-described enhancement processing of the luminance component, since the image contrast increases as the standard deviation σ of the Gaussian function increases, the luminance value decreases, resulting in an image color that is not sufficiently clear. In order to solve this problem, it is also necessary to process the saturation component of the original image.

In one example, in the above step 102, the saturation component may be enhanced by the following method:

It is found through experiments that the saturation component of the image is related to the reflected light information of the object in the luminance component. Therefore, the saturation component can be enhanced according to the relationship between the saturation component and the reflected light information of the object in the luminance component. The specific processing formula can be:

In order to enhance the processed saturation component, S is the saturation component of the original image, and R'(x, _y) is the reflected light information of the object after the global brightness adjustment, and the calculation formula of R'(x, _y) For:

K(x,y)= ^(x , + , Γ is the average brightness of the reflected light information of the object, introduced to avoid the phenomenon that the denominator is equal to 0, depending on the number of bits of the original image. For example, when the image When it is an 8-bit image, it is = / 255. Of course, in other embodiments of the present invention, the saturation component may be enhanced by other methods, and is not described here.

(3) color space conversion

In the Retinex visual model, the intrinsic property of the object itself is determined by the reflected illumination information of the object. Therefore, in the embodiment of the present invention, the influence of the ambient brightness function on the image is removed, and the processed reflected illumination information is used as the enhanced brightness. Component.

In an example, in the above step 103, the hue component of the original image ( ^x , the enhanced saturation component ( ^x , , and the processed reflected illumination information ( ^x , from the HSI color) may be used by the following formula: Space conversion to RGB color space:

When H(x, _y) < ² r/J, the three components of _RGB can be derived from:

B = R\x,y)[lS\x,y)]

Cos[_60° -H(x,y)~ G = 3R\x,y)-(R + B)

When 2^ ≤ ^^ < /_?, the first three components of RGB are subtracted from the following equation:

B = 3R\x, y)-(R + G)

When ^ /J ≤ H < ² r, first subtract H from W / , the three components of RGB can be obtained from

G = RXx, y) [l-S\x, y)]

S'(x,y)co H(x,y)

B = R\x, y) 1 + - cos[6 °_H(x, ]JR = 3R\x, y)-(G + B) Of course, in the above step 103, other conversion formulas are not excluded. Converts the processed image from the HSI color space to the RGB color space.

Referring to FIG. 3, in an embodiment, before performing local enhancement processing on the luminance component, the gray level of the luminance component may be normalized, and the image is converted into a preset variation range to obtain The processed luminance component is then subjected to local enhancement processing and global luminance adjustment for the normalized luminance component.

For example, for an 8-bit color image, after it is converted to the HSI color space, the luminance component of the image / (χ, the range of gray levels is [0, 255], in order to ensure data processing, grayscale is required. The level is normalized so that the gray level range of the original image becomes [0, 1], that is:

/(x, — min

If max [/(x, ] - min

Max [/(x, ] - min [l(x.

0 if max [/(x, ] - min where /(χ, is the normalized processed luminance component, /(χ, 3 is the luminance of the original image corresponds to the image enhancement method described above, and is still in the embodiment of the present invention) Providing an image enhancement device, such as As shown in FIG. 4, the image enhancement apparatus includes:

a first conversion module 401, configured to convert an original image from a red, green, and blue RGB color space to a hue, saturation, and brightness HSI color space;

The image enhancement module 402 is configured to maintain the tone component unchanged, and perform enhancement processing on the luminance component and the saturation component respectively to obtain the processed image;

The second conversion module 403 is configured to convert the processed image from the HSI color space to the RGB color space.

In an example, corresponding to the image enhancement method shown in FIG. 2, the image enhancement module may further include:

In an example, corresponding to the image enhancement method shown in FIG. 3, the image enhancement module may further include:

In an example, corresponding to the method shown in FIG. 2 and FIG. 3, the image enhancement module may further include:

In addition, an embodiment of the present invention further provides a display device, including the above image enhancement device, including but not limited to: a liquid crystal television, a computer, a mobile phone, and the like.

The above description is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can also make several improvements and retouchings without departing from the principles of the present invention. It is considered as the scope of protection of the present invention.

Claims

Claim

1. An image enhancement method, comprising:

Convert the original image from the red, green, and blue RGB color space to hue, saturation, and brightness HSI color space;

2. The image enhancement method according to claim 1, wherein said step of performing enhancement processing on the luminance component comprises:

The global brightness adjustment is performed on the locally enhanced image using a Gamma transform.

3. The image enhancement method according to claim 2, wherein the step of performing local enhancement processing on the luminance component by using the Retinex visual model further comprises:

4. The image enhancement method according to any one of claims 2-3, wherein:

进行 Locally enhancing the luminance component of the original image using the following formula:

t (x, y) = I(x, y) * G(x, y)

Where J' (x, _y) is the ambient brightness function after local enhancement processing, /(x, _y) is the luminance component of the original image, G(x, _y) is the Gaussian function, and the calculation of G(x, _y) The formula is:

^G ( ^x ' ⁼ , σ is the standard deviation of the Gaussian function;

Where , is the ambient brightness function after global brightness adjustment, and γ is the Gamma transform coefficient.

5. The image enhancement method according to claim 2, wherein the saturation component is enhanced by the following formula:

In order to enhance the processed saturation component, S is the saturation component of the original image, and R'(x, _y) is the global brightness-adjusted object-reflected illumination information, and the calculation formula of R'(x, _y) For:

K(x,y) = ^(x , + , Γ is the average brightness of the reflected light information of the object, depending on the number of bits of the original image, /(x, _y) is the luminance component of the original image, J; (x , the ambient brightness function adjusted for global brightness.

6. An image enhancement device comprising:

a second conversion module, configured to convert the processed image from an HSI color space to an RGB color space.

The image enhancement device according to claim 6, wherein the image enhancement module comprises: a local enhancement module, configured to perform local enhancement processing on a luminance component of the original image by using a Retinex visual model, and obtain a local enhancement process Image;

8. The image enhancement apparatus of claim 7, wherein the image enhancement module further comprises: a normalization processing module, configured to normalize a gray level of a luminance component of the original image to obtain a The luminance component is normalized, and the normalized luminance component is sent to the local enhancement module as a luminance component of the original image.

The image enhancement device according to any one of claims 6 to 8, wherein the image enhancement module further comprises:

A display device comprising the image enhancement device according to any one of claims 6 to 9.