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Proceedings Paper

Stripe noise reduction in MODIS data: a variational approach
Author(s): Ning Ma; Ze-ming Zhou; Li-min Luo; Min Wang
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Paper Abstract

According to the characteristics of MODIS data stripe noises, we propose a novel variational method for stripe noise reduction. First we find the detectors contaminated by stripe noises by separating MODIS data into several subimages due to the numbers of scan detectors. Then for subimages with stripe noises, we build an energy minimization problem by combining two energy terms to find the solution as the destriped result. The first energy term uses variational histogram matching method to remove detector-to-detector stripes and mirror side stripes while the second energy term uses non-linear anisotropic diffusion method to remove the random noise of noisy stripes. The gradient descent flow is applied to minimize the total energy functional and the numerical scheme is presented. Experimental results show that the method can reduce stripes noises effectively.

Paper Details

Date Published: 8 September 2011
PDF: 8 pages
Proc. SPIE 8193, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, 81933C (8 September 2011); doi: 10.1117/12.900759
Show Author Affiliations
Ning Ma, Southeast Univ. (China)
PLA Univ. of Science & Technology (China)
Ze-ming Zhou, PLA Univ. of Science & Technology (China)
Li-min Luo, Southeast Univ. (China)
Min Wang, PLA Univ. of Science & Technology (China)


Published in SPIE Proceedings Vol. 8193:
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications
Jeffery J. Puschell; Junhao Chu; Haimei Gong; Jin Lu, Editor(s)

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