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Proceedings Paper

An improved blind restoration algorithm for multiframe turbulence-degraded images
Author(s): Jing Guan; Jianchong Chen; Kejia Yi; Ze Wang
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Paper Abstract

This paper proposes an improved blind deconvolution algorithm, which adopts maximum likelihood method to find the most similar estimation of the PSF and object with Poisson-based probability model. The algorithm integrates Cauchy probability distribution model into the estimation of the PSF under the condition of low SNR, uses the characteristic of short-exposure image sequence that the adjacent images have similar PSF to get restored image with frames as few as possible. The experimental results show that this method is robust with high ability of resisting noise in the restoration of turbulence-degraded images.

Paper Details

Date Published: 8 December 2011
PDF: 8 pages
Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 80020W (8 December 2011); doi: 10.1117/12.901535
Show Author Affiliations
Jing Guan, Huazhong Univ. of Science and Technology (China)
Jianchong Chen, Huazhong Univ. of Science and Technology (China)
Kejia Yi, Harbin Engineering Univ. (China)
Ze Wang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 8002:
MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis
Faxiong Zhang; Faxiong Zhang, Editor(s)

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