Image restoration under significant additive noise

被引：16

作者：

Zhao, Wenyi ^{[1
]}

Pope, Art ^{[1
]}

机构：

[1] Sarnoff Corp, Princeton, NJ 08540 USA

来源：

IEEE SIGNAL PROCESSING LETTERS | 2007年 / 14卷 / 06期

关键词：

joint image segmentation and deblurring; non-local image averaging; significant additive noise; structure tensor;

D O I：

10.1109/LSP.2006.887843

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The task of deblurring, a form of image restoration, is to recover an image from its blurred version. Whereas most existing methods assume a small amount of additive noise, image restoration under significant additive noise remains an interesting research problem. We describe two techniques to improve the noise handling characteristics of a recently proposed variational framework for semi-blind image deblurring that is based on joint segmentation and deblurring. One technique uses a structure tensor as a robust edge-indicating function. The other uses nonlocal image averaging to suppress noise. We report promising results with these techniques for the case of a known blur kernel.

引用

页码：401 / 404

页数：4

共 17 条

[11] ITERATIVE IMAGE-RESTORATION ALGORITHMS [J].