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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/28163

Title: Fast hyperspectral image classification using binary quaternion-moment-preserving thresholding technique
Authors: Lena Chang;Ching-Min Cheng;Yang-Lang Chang
Contributors: NTOU:Department of Communications Navigation and Control Engineering
Date: 2008-07-06
Issue Date: 2011-10-21T02:36:04Z
Publisher: 2008 IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2008)
Abstract: Abstract:Recently, due to the advancement of remote sensors, optical remote sensing has been a significant increase in the number of spectral bands in acquired data, going from multispectral to hyperspectral. Hyperspectral imagery with hundreds of bands offers high spectral resolution and provides the potential accuracy in detection and classification of targets unresolved in multispectral images. However, higher spectral resolution increases the computation complexity in image processing. Thus, how to improve the accuracy with less computation complexity is the main challenge for hyperspectral image classification.
URI: http://ntour.ntou.edu.tw/handle/987654321/28163
Appears in Collections:[通訊與導航工程學系] 演講及研討會

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