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8 December 2011 An improved blind restoration algorithm for multiframe turbulence-degraded images
Jing Guan, Jianchong Chen, Kejia Yi, Ze Wang
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Proceedings Volume 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis; 80020W (2011) https://doi.org/10.1117/12.901535
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
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.
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Jing Guan, Jianchong Chen, Kejia Yi, and Ze Wang "An improved blind restoration algorithm for multiframe turbulence-degraded images", Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 80020W (8 December 2011); https://doi.org/10.1117/12.901535
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KEYWORDS
Point spread functions
Signal to noise ratio
Deconvolution
Evolutionary algorithms
Image restoration
Detection and tracking algorithms
Image analysis
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