Image blind deblurring method based on dark channel prior and multi direction weighted TV (total variation)

Abstract

The invention discloses an image blind deblurring method based on a dark channel prior and a multi direction weighted TV(total variation), which mainly comprises steps of constructing an image blind restoration model and its solution, and finally obtaining a target image and a fuzzy kernel. The method of the invention aims at the problem that the total variation (TV) regularized image restorationhas the limited detail recovery capability and is sensitive to noise. In the method, multi-directional edge detection is utilized, the conventional TV model is improved, and a multi-direction weightedTV model based on edge detection is obtained; at the same time, in order to make the recovery model more universal and improve the detail recovery capability, the dark channel priors is fused into the above multi-direction weighted TV model. Experiments show that the target image restored by the method of the present invention has a perfect visual effect, the local smoothness of the image is maintained, the details such as the edge and texture of the image can be well restored, the ring effect is significantly reduced, and the fuzzy kernel estimation is more accurate.

Description

technical field [0001] The invention relates to a computer image processing method, in particular to an image deblurring method. Background technique [0002] Image deblurring has always been a research hotspot in the field of computer vision and image processing, and has attracted much attention because of its cutting-edge and wide application. [0003] Among many deblurring methods, total variation (TV) regularization is widely used in image denoising, image deblurring, etc. [1,2] , but its detail and texture recovery capabilities are limited. Therefore, many TV regularization improvement methods have emerged, such as weighted TV regularization, which improves the detail recovery ability of the TV model by applying different weights to the smooth area of ​​​​the image and the edge of the image. [3] . [0004] On the other hand, the prior information of the traditional TV model is not suitable for specific images, such as face images, text images and low-light images, et...

AI Technical Summary

Problems solved by technology

[0014] Aiming at the problems of limited detail recovery ability and noise sensitivity of total variation (TV) regularized image restoration, the present invention provides a blind image deblurring method based on dark channel prior and multi-directional weighted TV (DCP-MDWTV), Using multi-directional edge detection, the traditional TV model is improved to obtain a multi-directional weighted TV model based on edge detection, and the dark channel prior is integrated into the above model to make the restoration model more universal and improve the ability to restore details

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