Method for restoring weighting sparse edge regularization image

An image and edge technology, which is applied in the field of computer image processing, can solve problems such as low restoration quality, neglect of image edge characteristics, and insufficient sharpness of restored image edges, so as to achieve the effect of enriching information and avoiding singularity problems

Inactive Publication Date: 2011-08-10
CHONGQING UNIV
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AI Technical Summary

Problems solved by technology

[0005] In the existing regularization methods based on image edge information, most methods only use the horizontal and vertical directions of the image, and the edge information in the two directions is used as the regularization item of the cost

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  • Method for restoring weighting sparse edge regularization image
  • Method for restoring weighting sparse edge regularization image
  • Method for restoring weighting sparse edge regularization image

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Embodiment Construction

[0094] As shown in Figure 2(b), the known information of the method of the present invention is the blurred noise image to be restored and a linear degradation function , where the blurred noise image is the "Lena" standard test image of size, and the linear degradation function In order to adopt uniform blurring, additive white Gaussian noise (BSNR=40dB) with mean value of 0 and variance of 0.3136 is added at the same time. Firstly, the horizontal direction, vertical direction, 45° angle direction and 135° angle direction are performed on each pixel in the fuzzy noise image, and the first-order difference operation in the four directions is obtained to obtain the first-order gradient information of the entire image. The calculation process is as follows:

[0095] (12)

[0096] in Represents an image with a size of , represents the coordinates in the image, and the pixel value of the corresponding pixel, Indicates the first-order gradient of the pix...

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Abstract

The invention discloses a method for restoring a weighting sparse edge regularization image, which comprises the following steps: (1) using a difference operator to obtain gradient information of each direction of a blurred noise image and combining directions at random so as to obtain a matrix mathematical model of the edge of the image; (2) according to an image sparse principle and the definition of the optimal sparse solution of an uncertain equation, aiming at an image edge model obtained in the step (1), adopting a weighting sparse constraint to constrain the edge of the image, and deriving the cost function of image restoration by combining a known degenerate function; and (3) according to the steps (1) and (2), using an improved upper bound minimal method to carry out optimization solving on the cost function so as to obtain a clear restored image. The method greatly enriches information content at the edge of the image; the weighting sparse edge constraint is adopted for effectively protecting the edge characteristics of the image; and the restored image with high quality is obtained by using the improved upper-bound minimal mathematical method.

Description

technical field [0001] The invention belongs to computer image processing technology and relates to an image restoration method. Background technique [0002] Image degradation is ubiquitous, and it exists in almost all fields related to image processing. In the process of acquiring images, the image blur caused by the mismatch between the object distance and the image distance between the camera device and the object to be photographed is called defocus blur; due to the relative motion between the imaging device and the object to be photographed Image blur is called motion blur. At the same time, the image will also be blurred due to external weather, sunlight, air, dust on the lens of the imaging device, and the hardware of the imaging device itself. In order to mine more and more accurate information from damaged images, a series of image processing technologies such as image clarity restoration and ultra-high resolution reconstruction have been widely studied and succes...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 龚卫国唐述李伟红李权利牟琳刘良辰
Owner CHONGQING UNIV
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