SUPERPIXEL-BASED MARKOV RANDOM FIELD FOR CLASSIFICATION OF HYPERSPECTRAL IMAGES

被引：22

作者：

Li, Shanshan ^{[1
]}

Jia, Xiuping ^{[2
]}

Zhang, Bing ^{[1
]}

机构：

[1] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing, Peoples R China

[2] Univ New S Wales, Australian Def Force Acad, Canberra, ACT, Australia

来源：

2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2013年

关键词：

Hyperspectral; MRF; superpixel; classification;

D O I：

10.1109/IGARSS.2013.6723581

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The paper presents a supervised classification method based on superpixels and Markov random field (MRF). Hyperspectral image is over-segmented into superpixels that are as basic unit of Markov random field instead of operating at the pixel level. Adaptive weight coefficient is introduced to determine contextual relationship between superpixels. Support vector machines are implemented for better estimation of spectral contribution to this approach. An experiment of real hyperspectral image reveals efficient performance.

引用

页码：3491 / 3493

页数：3

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