New Tikhonov Regularization for Blind Image Restoration

被引：2

作者：

Shi, Yuying ^{[1
]}

Liu, Qiao ^{[1
]}

Zhu, Yonggui ^{[2
]}

机构：

[1] North China Elect Power Univ, Dept Math & Phys, Beijing 102206, Peoples R China

[2] Commun Univ China, Sch Sci, Beijing 100024, Peoples R China

来源：

IMAGE AND GRAPHICS (ICIG 2017), PT III | 2017年 / 10668卷

关键词：

DEBLURRING MODELS; ROBUST ALGORITHM; DECONVOLUTION; IDENTIFICATION;

D O I：

10.1007/978-3-319-71598-8_11

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Blind image restoration is a challenging problem with unknown blurring kernel. In this paper, we propose a new algorithm based on a new Tikhonov regularization term, which combines three techniques including the split Bregman technique, fast Fourier transform and spectral decomposition technology to accelerate the computation process. Numerical results demonstrate that the proposed algorithm is simple, fast and effective for blind image restoration.

引用

页码：113 / 123

页数：11

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