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Proceedings Paper

A simulated annealing band selection approach for hyperspectral imagery
Author(s): Jyh Perng Fang; Yang-Lang Chang; Hsuan Ren; Chun-Chieh Lin; Wen-Yew Liang; Jwei-Fei Fang
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Paper Abstract

For hyperspectral imagery, greedy modular eigenspaces (GME) has been developed by clustering highly correlated hyperspectral bands into a smaller subset of band modules based on greedy algorithm. Instead of greedy paradigm as adopted in GME approach, this paper introduces a simulated annealing band selection (SABS) approach for hyperspectral imagery. SABS selects sets of non-correlated hyperspectral bands for hyperspectral images based on simulated annealing (SA) algorithm while utilizing the inherent separability of different classes in hyperspectral images to reduce dimensionality and further to effectively generate a unique simulated annealing module eigenspace (SAME) feature. The proposed SABS features: (1) avoiding the bias problems of transforming the information into linear combinations of bands as does the traditional principal components analysis (PCA); (2) selecting each band by a simple logical operation, call SAME feature scale uniformity transformation (SAME/FSUT), to include different classes into the most common feature clustered subset of bands; (3) providing a fast procedure to simultaneously select the most significant features according to SA scheme. The experimental results show that our proposed SABS approach is effective and can be used as an alternative to the existing band selection algorithms.

Paper Details

Date Published: 25 October 2006
PDF: 10 pages
Proc. SPIE 6378, Chemical and Biological Sensors for Industrial and Environmental Monitoring II, 63781G (25 October 2006); doi: 10.1117/12.685683
Show Author Affiliations
Jyh Perng Fang, National Taipei Univ. of Technology (Taiwan)
Yang-Lang Chang, National Taipei Univ. of Technology (Taiwan)
Hsuan Ren, National Central Univ. (Taiwan)
Chun-Chieh Lin, National Taipei Univ. of Technology (Taiwan)
Wen-Yew Liang, National Taipei Univ. of Technology (Taiwan)
Jwei-Fei Fang, National Taichung Univ. (Taiwan)


Published in SPIE Proceedings Vol. 6378:
Chemical and Biological Sensors for Industrial and Environmental Monitoring II
Steven D. Christesen; Arthur J. Sedlacek; James B. Gillespie; Kenneth J. Ewing, Editor(s)

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