Technology and Methodology |
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Hyperspectral images classification based on MKSVM and MRF |
TAN Xiong1,2, YU Xuchu1, ZHANG Pengqiang1, FU Qiongying1, WEI Xiangpo1, GAO Meng1 |
1. Information Engineering University, Zhengzhou 450001, China; 2. Jiangxi Province Key Lab for Digital Land, East China Institute of Technology, Nanchang 330000, China |
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Abstract To fully utilize the spectral and spatial information rich in hyperspectral remote sensing images, this paper proposes a hyperspectral images classification method based on multiple kernel support vector machine (MKSVM) and Markov random field (MRF). Firstly, the MKSVM classifier is used to classify hyperspectral images, then the MRF is used to regularize the initial classification results in the spatial structure, and the final classification results are obtained in the end. The experiment on AVIRIS hyperspectral image shows that the proposed method not only effectively eliminates the "noise" in the homogeneous regions within the classification results but also improves the classification accuracy by about 3%.
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Keywords
IKONOS2
Juhugeng coal mine
remote sensing monitoring
mine geological environment quality
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Issue Date: 23 July 2015
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