Efficient Blind Image Deblurring Method Based on Edge Adaptation

Abstract

The invention discloses an image blind deblurring method based on edge self-adaption. To solve the problems that as for an existing total variation deblurring algorithm, edges and details of images are easily blurred, a de-mean gradient total variation canonical model is built, weighting coefficients are calculated in an iterated mode by means of local variance self-adaption of gradients of the images, and the ability of the deblurring algorithm to restore the edges and the details of the images. The image blind deblurring method comprises the following steps that (1) a blurred image is input, solutions to a gradient-region clear image and a blurring kernel are obtained alternately, and the initial blurring kernel of the blurred image is obtained; (2) the initial blurring kernel is used for conducting primary non-blind deblurring on the blurred image, and an initial clear image is obtained; (3) clustering is conducted on the initial clear image, the mean value and the weighting coefficient in the de-mean canonical model are updated, and a solution to the blurring kernel is obtained again; (4) the new blurring kernel is used for conducting secondary non-blind deblurring so as to obtain a clear image. Experimental results show that the image blind deblurring method based on edge self-adaption has better deburring effect than the prior art and can be used for image restoration.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a blind image deblurring method, which can be used for image restoration. Background technique [0002] During the camera imaging process, due to camera shake, defocus, defocus, or target object movement, the photos taken by people are often blurred. Restoring a clear digital image from a single blurred image has important requirements in digital media entertainment, national defense and security. Usually, the information such as the motion parameters of the camera relative to the scene is unknown. In order to remove the blur of the image, it is necessary to estimate the blur kernel of the image and the clear digital image at the same time. Deblurring the image when the blur kernel is unknown is the blind image removal. Blurring, image blind deblurring is a relatively difficult image restoration problem. [0003] The image blind deblurring problem can be expressed as ...

AI Technical Summary

Problems solved by technology

In order to obtain a clear image, it is usually necessary to use some complicated methods to sharpen the edges of the image, but this method is not only complicated, but also difficult to guarantee its feasibility in theory and effect

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