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

Author

Yan, Luxin ; Jin, Mingzhi ; Fang, Houzhang ; Liu, Hai ; Zhang, Tianxu

Author_Institution

Nat. Key Lab. of Sci. & Technol. on Multispectral Inf. Process., Huazhong Univ. of Sci. & Technol., Wuhan, China

Volume

9

Issue

4

fYear

2012

fDate

7/1/2012 12:00:00 AM

Firstpage

672

Lastpage

676

Abstract

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.

Keywords

atmospheric turbulence; geophysical image processing; image restoration; atmospheric-turbulence-degraded astronomical image restoration; finite-extent object; finite-support images; image SOCM; imaging systems; nonuniform index-of-refraction; second-order central moment; uniformly black background; uniformly gray background; uniformly white background; wave propagation virtue; Atmospheric modeling; Image restoration; Minimization; Noise measurement; PSNR; Pattern recognition; Atmospheric turbulence; blur identification; image restoration; second-order central moment (SOCM);

fLanguage

English

Journal_Title

Geoscience and Remote Sensing Letters, IEEE

Publisher

ieee

ISSN

1545-598X

Type

jour

DOI

10.1109/LGRS.2011.2178016

Filename

6138288