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Proceedings Paper

Improving the quality of remote sensing images using a universal reconstruction method
Author(s): Huanfeng Shen; Tinghua Ai; Pingxiang Li; Yi Wang
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Paper Abstract

This paper presents a universal maximum a posteriori (MAP) based reconstruction method which can be used for destriping, inpainting (the removal of dead pixels) and super resolution reconstruction (the recovery of a high resolution image from several low resolution images). In the MAP framework, the likelihood probability density function (PDF) is constructed based on a linear image observation model, and a robust Huber-Markov model is used as the prior PDF. A gradient descent optimization method is employed to produce the desired image. The proposed algorithm has been tested using MODIS images for destriping and super resolution reconstruction, and CBERS (China-Brazil Earth Resource Satellite) and QuickBird images for simulated inpainting. The experiment results and quantitative analyses verify the efficacy of this algorithm.

Paper Details

Date Published: 29 December 2008
PDF: 7 pages
Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851G (29 December 2008); doi: 10.1117/12.816609
Show Author Affiliations
Huanfeng Shen, Wuhan Univ. (China)
Tinghua Ai, Wuhan Univ. (China)
Pingxiang Li, Wuhan Univ. (China)
Yi Wang, China Univ. of Geosciences (China)


Published in SPIE Proceedings Vol. 7285:
International Conference on Earth Observation Data Processing and Analysis (ICEODPA)
Deren Li; Jianya Gong; Huayi Wu, Editor(s)

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