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Low-light image enhancement method based on red green blue (RGB) color model

A color model, image enhancement technology, applied in image enhancement, image data processing, instruments, etc., to reduce noise, make up for lost image edge information, and improve image quality.

Inactive Publication Date: 2013-01-30
XIDIAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0012] The object of the present invention is to aim at the shortcoming of traditional histogram equalization method, propose a kind of low light image enhancement method based on RGB color model, to improve the quality of low light image

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  • Low-light image enhancement method based on red green blue (RGB) color model
  • Low-light image enhancement method based on red green blue (RGB) color model
  • Low-light image enhancement method based on red green blue (RGB) color model

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Embodiment Construction

[0042] Combine below figure 1 The specific implementation steps of the present invention are described in further detail:

[0043] Step 1. Extract R, G, B component images and perform fast Fourier transform.

[0044] In the embodiment of the present invention, a low-light image is input, and the image size is 1074×2272×3. Based on the principle of the RGB color model, the R component image fR(x,y), the G component image fG(x,y) and the B component image fB(x,y) of the image are extracted, and fR(x,y), fG (x, y) and fB(x, y) undergo fast Fourier transform respectively to obtain transformed R component image FR(u,v), G component image FG(u,v) and B component image FB(u , v).

[0045] Step 2. Perform frequency division processing on FR(u, v), FG(u, v) and FB(u, v) described in step 1.

[0046] In an embodiment of the present invention, we use a Gaussian low-pass filter with a cutoff frequency of 40 to process the R component image FR(u,v), the G component image FG(u,v) and th...

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Abstract

The invention provides a low-light image enhancement method based on a red green blue (RGB) color model. The problems that in the prior art, image detail information and marginal information are ignored or lost are solved. During the process that low-light image color information is applied to image enhancement, the method comprises steps of extracting and inputting R, G and B component images of an image; conducting frequency division for R, G and B component images; conducting histogram equalization for low frequency components of R, G and B component images; conducting weighting for high frequency components of R, G and B component images; conducting linear combination for processed low frequency components and high frequency components and obtaining processed R, G and B component images; and combining processed R, G and B component images and outputting a final enhanced image. Accordingly, the illumination of the image is improved, the noise in the image is reduced effectively, the detail information and the marginal information of the image are retained well, and the quality of a color image which is shot under the condition of insufficient light is improved.

Description

technical field [0001] The invention relates to image enhancement processing, in particular to a low light image enhancement method, which can be used to improve the quality of color images taken under insufficient light conditions. Background technique [0002] The main purpose of image enhancement is to improve the visual quality of an image. For a given image, image enhancement can use some special technology to highlight some information in the image, weaken or eliminate some useless information according to the blurring of the image and the application occasion, so as to achieve purposeful emphasis. The effect of global or local features of an image. Enhanced images often help observers to identify special information, that is, allow observers to see more direct, clear and suitable information for analysis. It should be particularly mentioned that the quality of the enhanced image is mainly evaluated by human vision, and visual evaluation is highly subjective. For a ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T5/40
Inventor 张梦璇焦李成闫允一王爽尚荣华马文萍马晶晶李阳阳于昕
Owner XIDIAN UNIV
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