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Proceedings Paper

Classification of multi-spectral remote sensing images based on hidden Markov models
Author(s): Hui Wang; Jian Lu
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Paper Abstract

This paper presents the analogy between voice recognition and multi-spectral remote sensing image classification, and introduces the Hidden Markov Model (HMM), which is a successful approach on voice recognition fields, into multi-spectral remote sensing image classification. After comparing the HMM with other conventional classification methods such as Maximum Likelihood and Minimum Distance, the paper concludes that the HMM is a better approach than other techniques do. At the end of the paper, the author explains the reason of HMM's good performance, and also points out its defect.

Paper Details

Date Published: 3 November 2005
PDF: 6 pages
Proc. SPIE 6043, MIPPR 2005: SAR and Multispectral Image Processing, 604325 (3 November 2005); doi: 10.1117/12.654982
Show Author Affiliations
Hui Wang, Wuhan Univ. School of Remote Sensing Information Engineering (China)
Jian Lu, Wuhan Univ. School of Remote Sensing Information Engineering (China)


Published in SPIE Proceedings Vol. 6043:
MIPPR 2005: SAR and Multispectral Image Processing
Liangpei Zhang; Jianqing Zhang; Mingsheng Liao, Editor(s)

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