A Novel Adaptive Compression Method for Hyperspectral Images by using EDT and Particle Swarm Optimization

Title
A Novel Adaptive Compression Method for Hyperspectral Images by using EDT and Particle Swarm Optimization
Publication Date
2012
Author(s)
Ghamisi, Pedram
Kumar, Lalit
( author )
OrcID: https://orcid.org/0000-0002-9205-756X
Email: lkumar@une.edu.au
UNE Id une-id:lkumar
Editor
Editor(s): Sebastiano Battiato, Brian G Rodricks, Nitin Sampat, Francisco H Imai, Feng Xiao
Type of document
Conference Publication
Language
en
Entity Type
Publication
Publisher
International Society for Optical Engineering (SPIE)
Place of publication
United States of America
Series
Proceedings of SPIE
DOI
10.1117/12.904727
UNE publication id
une:10087
Abstract
Hyperspectral sensors generate useful information about climate and the earth surface in numerous contiguous narrow spectral bands, and are widely used in resource management, agriculture, environmental monitoring, etc. Compression of the hyperspectral data helps in long-term storage and transmission systems. Lossless compression is preferred for high-detail data, such as hyperspectral data. Due to high redundancy in neighboring spectral bands and the tendency to achieve a higher compression ratio, using adaptive coding methods for hyperspectral data seems suitable for this purpose. This paper introduces two new compression methods. One of these methods is adaptive and powerful for the compression of hyperspectral data, which is based on separating the bands with different specifications by the histogram and Binary Particle Swarm Optimization (BPSO) and compressing each one a different manner. The new proposed methods improve the compression ratio of the JPEG standards and save storage space the transmission. The proposed methods are applied on different test cases, and the results are evaluated and compared with some other compression methods, such as lossless JPEG and JPEG2000.
Link
Citation
Digital Photography VIII, p. 82990M-1-82990M-12
ISBN
9780819489463
Start page
82990M-1
End page
82990M-12

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