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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/28118

Title: A Combined Signal Subspace Projection and Partial Filtering Approach to Target Detection for Hyperspectral images
Authors: Lena Chang;Ching-Min Cheng;F. W. Tseng
Contributors: 國立臺灣海洋大學:通訊與導航工程學系
Date: 2006-07-31
Issue Date: 2011-10-21T02:35:56Z
Publisher: 2006 IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2006)
Abstract: In the study, a novel signal subspace projection
(SSP) approach is first proposed to detect and extract target signatures in unknown background. The weights of SSP are equivalent to optimal weights given by Wiener-Hopf equations. To further reduce the computation complexity in
SSP, we implement the SSP-based classifier by an adaptive filter combined with some partial filters, called CSSPPF. In CSSPPF, we partition the image into several groups according to their associated band correlation. By the way,we transfer the design of a large fully filter into several small partial filter designing. Simulation results performed on AVIRIS images have demonstrated the efficiency of the
proposed approaches.
Relation: pp.3891-3894
URI: http://ntour.ntou.edu.tw/handle/987654321/28118
Appears in Collections:[通訊與導航工程學系] 期刊論文

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