A computational method for the restoration of images with an unknown, spatially-varying blur

被引：53

作者：

Bardsley, J ^{[1
]}

Jefferies, S

Nagy, J

Plemmons, R

机构：

[1] Univ Montana, Dept Math Sci, Missoula, MT 59812 USA

[2] Univ Hawaii, Astron Inst, Kula, HI 96790 USA

[3] Emory Univ, Dept Math & Comp Sci, Atlanta, GA 30322 USA

[4] Wake Forest Univ, Dept Comp Sci & Math, Winston Salem, NC 27109 USA

来源：

OPTICS EXPRESS | 2006年 / 14卷 / 05期

关键词：

D O I：

10.1364/OE.14.001767

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

In this paper, we present an algorithm for the restoration of images with an unknown, spatially-varying blur. Existing computational methods for image restoration require the assumption that the blur is known and/or spatially-invariant. Our algorithm uses a combination of techniques. First, we section the image, and then treat the sections as a sequence of frames whose unknown PSFs are correlated and approximately spatially-invariant. To estimate the PSFs in each section, phase diversity is used. With the PSF estimates in hand, we then use a technique by Nagy and O'Leary for the restoration of images with a known, spatially-varying blur to restore the image globally. Test results on star cluster data are presented. (c) 2006 Optical Society of America.

引用

页码：1767 / 1782

页数：16

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