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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/28331

Title: A group and region based compression method for hyperspectral imagery
Authors: Lena Chang;Ching-Min Cheng;Yang-Lang Chang;Bo-Wei Lee
Contributors: NTOU:Department of Communications Navigation and Control Engineering
Keywords: hyperspectral image;image compression;segmentation;Karhunen-Loeve transform (KLT)parallel architecture
Date: 2010-07-25
Issue Date: 2011-10-21T02:37:06Z
Publisher: Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Abstract: Abstract:In the study, an efficient compression approach, group and region based KLT (GR-KLT), is proposed for hyperspectral imagery. The GR-KLT contains one clustering signal subspace projection (CSSP) segmentation method and the maximum correlation band clustering (MCBC) method. The CSSP first divides the image into proper regions and the MCBC partitions the spectral bands into several groups according to their associated band correlation for each image region. By the way, the image is further compressed by the KLT-JPEG for each group in each image region. Furthermore, we develop a parallel architecture for the GR-KLT compression algorithm. Simulation results performed on AVIRIS images have demonstrated the efficiency of the proposed approaches.
Relation: pp. 181-184
URI: http://ntour.ntou.edu.tw/handle/987654321/28331
Appears in Collections:[通訊與導航工程學系] 演講及研討會

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