Atmospheric-Turbulence-Degraded Astronomical Image Restoration by Minimizing Second-Order Central Moment

被引：29

作者：

Yan, Luxin ^{[1
]}

Jin, Mingzhi ^{[1
]}

Fang, Houzhang ^{[1
]}

Liu, Hai ^{[1
]}

Zhang, Tianxu ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Inst Pattern Recognit & Artificial Intelligence, Natl Key Lab Sci & Technol Multispectral Informat, Wuhan 430074, Peoples R China

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2012年 / 9卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Atmospheric turbulence; blur identification; image restoration; second-order central moment (SOCM); PATTERN-RECOGNITION; BLUR; INVARIANTS;

D O I：

10.1109/LGRS.2011.2178016

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Atmospheric turbulence affects imaging systems by virtue of wave propagation through a medium with a nonuniform index of refraction. It can lead to blurring in images acquired from a long distance away. In this letter, it is observed that blurring increases the second-order central moment (SOCM) of images, and we introduce a new parametric blur identification method by minimizing SOCM. The method applies to finite-support images, in which the scene consists of a finite-extent object against a uniformly black, gray, or white background. The SOCM method has been validated by direct comparisons with other methods on simulated and real degraded images.

引用

页码：672 / 676

页数：5

共 9 条

[1]

[Anonymous], 2006, Digital Image Processing

[2] IMAGE FEATURES INVARIANT WITH RESPECT TO BLUR [J].