GAO R X, ZHU X L, WU Z H, et al.Adaptive iterative blind image restoration based on combining regularization and low rank prior[J].Journal of Henan Polytechnic University(Natural Science) ,2023,42(5):137-143.

doi:10.16186/j.cnki.1673-9787.2021070053

Received:2021/07/15

Revised:2022/01/27

Published:2023/09/25

Adaptive iterative blind image restoration based on combining regularization and low rank prior

GAO Ruxin1,2,3, ZHU Xinliu1,2,3, WU Zhonghua1,2,3, TAN Xingguo1,4

1.School of Electrical Engineering and Automation，Henan Polytechnic University，Jiaozuo  454000，Henan，China;2.Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment，Jiaozuo  454000，Henan，China;3.Henan International Joint Laboratory of Direct Drive and Control of Intelligent Equipment，Jiaozuo  454000，Henan，China;4.Hami Polytechnic，Hami  839000，Xinjiang，China

Abstract:In order to improve the effect of blind restoration of motion blur images and solve the problems of obvious artifacts，poor robustness，and unfavorable kernel estimation due to fixed iteration number at various scales，an adaptive iterative blind image restoration algorithm based on combining regularization and low-rank prior was proposed.Firstly，the sparseness of l₀ regularized prior was used to estimate the intermediate restored image and effectively remove the artifacts.Meanwhile，a low-rank prior was introduced to suppress the noise interference in the process of latent image restoration and improve the accuracy of blur kernel estimation.Secondly，an adaptive strategy was adopted to evaluate the similarity of blur kernel to adjust the number of iterations at different scales.Finally，an alternative optimization strategy based on semi-quadratic splitting was used to solve the algorithm model，and the final clear image was obtained by non-blind deblurring method.Experimental results showed that the proposed algorithm can effectively suppress noise and artifacts，and had good robustness and good restoration effect.

Key words:blind image deblurring;regularization;low rank prior;adaptive iteration;blur kernel estimation

联合正则化与低秩先验的自适应迭代盲图像复原_高如新.pdf