Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/9896
Title: A Novel Adaptive Compression Method for Hyperspectral Images by using EDT and Particle Swarm Optimization
Contributor(s): Ghamisi, Pedram (author); Kumar, Lalit  (author)orcid 
Publication Date: 2012
DOI: 10.1117/12.904727
Handle Link: https://hdl.handle.net/1959.11/9896
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.
Publication Type: Conference Publication
Conference Name: IS&T/SPIE Electronic Imaging, California, United States of America, 22nd - 26th January, 2012
Conference Details: IS&T/SPIE Electronic Imaging, California, United States of America, 22nd - 26th January, 2012
Source of Publication: Digital Photography VIII, p. 82990M-1-82990M-12
Publisher: SPIE: International Society for Optical Engineering and IS&T: The Society for Imaging Science and Technology
Place of Publication: United States of America
Field of Research (FOR): 090905 Photogrammetry and Remote Sensing
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Series Name: Proceedings of SPIE
Series Number : 8299
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