Enhanced RL-IBD algorithm for image restoration

Bo Chen; Ze-xun Geng; Shu-long Zhu; Yang Yang

doi:10.1117/12.815892

29 December 2008 Enhanced RL-IBD algorithm for image restoration

Bo Chen, Ze-xun Geng, Shu-long Zhu, Yang Yang

Proceedings Volume 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA); 72851M (2008) https://doi.org/10.1117/12.815892
Event: International Conference on Earth Observation Data Processing and Analysis, 2008, Wuhan, China

Abstract

The performance of high-resolution imaging with large optical instruments is severely limited by atmospheric turbulence. Image deconvolution such as iterative blind deconvolution (IBD) and Richardson-Lucy (RL) deconvolution are required. The IBD method involves the imposition of constraints such as conservation of energy, positivity, and finite support, with known size, alternately on the image and the PSF in the spatial and Fourier domains, until convergence. The iterative RL solution converges to the maximum likelihood solution for Poisson statistics in the data. Properties of the RL algorithm which make it well-suited for IBD are energy conservation and the sustenance of nonnegativity. So, RL was incorporated into the IBD framework. In this paper, an enhanced Richardson-Lucy-based iterative blind deconvolution (ERL-IBD) algorithm is proposed to restore the blurred images due to atmospheric turbulence. The ERLIBD incorporates dynamic PSF support estimation, bandwidth constraint of optical system, and the asymmetry factor update. The experimental results demonstrate that the ERL-IBD algorithm works better than IBD algorithm in deconvolution of the blurred-turbulence image.

Citation Download Citation

Bo Chen, Ze-xun Geng, Shu-long Zhu, and Yang Yang "Enhanced RL-IBD algorithm for image restoration", Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851M (29 December 2008); https://doi.org/10.1117/12.815892

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available