测试科学与仪器2023，Vol.14Issue(2)：182-188,7.DOI:10.3969/j.issn.1674-8042.2023.02.007
基于l1/l2正则化的图像盲去模糊方法
Blind image deblurring method based on l1/l2-norm regularization
摘要
Abstract
Aiming at the problem of ringing artifacts existing in the edge of image in traditional blind image deblurring methods,l1/l2 regularization-based blind image deblurring method is proposed.The latent image is constrained by l1/l2 regularization,and the two-norm constraint is applied to the blur kernel to remove the noise of the blur kernel.During the solution process,the latent image and the blur kernel are updated alternately and iteratively,and the deblurred image is finally obtained by combining the finest estimated blur kernel with the non-blind deblurring method.The experimental results show that the proposed method improves the quality of image deblurring and effectively removes some ringing artifacts.It has a good restoration effect on natural blurred images.关键词
图像盲去模糊/正则化/快速迭代收缩阈值/快速傅里叶变换Key words
blind image deblur/regularization/fast iterative contraction threshold/fast Fourier transform引用本文复制引用
曹胜芳,胡红萍,王文科..基于l1/l2正则化的图像盲去模糊方法[J].测试科学与仪器,2023,14(2):182-188,7.基金项目
Basic Research Program of Shanxi Province(No.20210302123019) （No.20210302123019）
Scientific Research Project for Returned Overseas Chinese in Shanxi Province(Nos.2020-104,2021-108). （Nos.2020-104,2021-108）
