Title : 
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
         
        
        
        
        
            fDate : 
7/1/2012 12:00:00 AM
         
        
        
        
            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);
         
        
        
            Journal_Title : 
Geoscience and Remote Sensing Letters, IEEE
         
        
        
        
        
            DOI : 
10.1109/LGRS.2011.2178016