Detecting Burnscar from Hyperspectral Imagery via Sparse Representation with Low-Rank Interference release_swb7mtanrzasbbmks7u4yxukoi

by Minh Dao, Xiang Xiang, Bulent Ayhan, Chiman Kwan, Trac D. Tran

Released as a article .

2016  

Abstract

In this paper, we propose a burnscar detection model for hyperspectral imaging (HSI) data. The proposed model contains two-processing steps in which the first step separate and then suppress the cloud information presenting in the data set using an RPCA algorithm and the second step detect the burnscar area in the low-rank component output of the first step. Experiments are conducted on the public MODIS dataset available at NASA official website.
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Date   2016-05-01
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arXiv  1605.00287v1
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