Priority constraint colorful image sparse expression restoration method

A color image, sparse representation technology, applied in the field of color image sparse representation restoration, can solve the problems of weighted image blocks blurring, wrong matching, etc.

Inactive Publication Date: 2016-08-31
HANGZHOU DIANZI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although many improvements have been made to this method at present, there will still be erroneous matching and blurring caused by too many weighted image blocks.

Method used

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  • Priority constraint colorful image sparse expression restoration method
  • Priority constraint colorful image sparse expression restoration method
  • Priority constraint colorful image sparse expression restoration method

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Embodiment Construction

[0066] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0067] In this example, figure 1 A flow diagram of the invention is given.

[0068] The first step: first use the conversion formula between the RGB color model and the YUV color model to map the image from the RGB space to the YUV space. The YUV model uses brightness and chroma to represent color information, where Y represents brightness, U and V represent chroma, and the three components are independent of each other. The conversion relationship between the brightness Y in the YUV model and the R, G, and B three color components in the RGB model can be expressed as:

[0069] Y=0.3R+0.59G+0.11B (1)

[0070] The chromaticity information U and V are mixed by B-Y and R-Y in different proportions. After Gamma calibration, the conversion formula between the models is:

[0071] Y ...

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Abstract

The invention discloses a priority constraint colorful image sparse expression restoration method. The method comprises steps that step 1, a colorful image is mapped from an RGB color space to a YUV color space, and three-layer component restoration is respectively carried out; step 2, a Fast-ICA algorithm is utilized for training to acquire a complete dictionary; step 3, priority of all edge points of a broken area of a to-be-restored image is calculated, and the restoration priority sequence is determined; step 4, in combination with an SL0 algorithm, sparse reconstruction of the broken block is carried out; and step 5, edge update is carried out, and the step 3 and the step 4 are repeated till image restoration is accomplished. The method is advantaged in that image restoration quality is high, the edge structure after image restoration has relatively good continuity, and image integrity is further kept.

Description

technical field [0001] The invention belongs to the technical field of digital image restoration, and in particular relates to a color image sparse representation restoration method with priority constraints in the image restoration technology. Background technique [0002] At present, the restoration of color images is mainly based on directly extending the restoration method of grayscale images to the RGB three components of color images. Traditional grayscale image inpainting methods are divided into two categories: one is based on partial differential equations. This method essentially diffuses information according to the direction of the isoluminance line, and the repair effect is close to the human visual experience, but this method can only repair images with small damaged blocks. The other is the method based on texture synthesis. The method is to find the best matching block in the undamaged area to replace the block to be repaired, and a wrong match will be gene...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T5/005G06T2207/10024G06T2207/20192
Inventor 唐向宏张少鹏李齐良
Owner HANGZHOU DIANZI UNIV
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