Binary Hybrid GA-PSO based algorithm for compression of hyperspectral data

Author

Ghamisi, Pedram ; Sepehrband, Farshid ; Choupan, Jayran ; Mortazavi, Mohammad

Author_Institution

Geodesy & Geomatics Eng. Fac., K.N. Toosi Univ. of Technol., Tehran, Iran

fYear

2011

fDate

12-14 Dec. 2011

Firstpage

1

Lastpage

8

Abstract

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 analyzes and new version of Binary Hybrid GA-PSO (BHGAPSO) and compressing each one with a different manner. The new proposed methods improve the compression ratio of the JPEG standards and save storage space the transmission system. 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.

Keywords

data compression; geophysical image processing; image coding; JPEG standard; JPEG2000; binary hybrid GA-PSO; compression ratio; histogram analysis; hyperspectral data compression; Correlation; Entropy; Histograms; Hyperspectral imaging; Image coding; Optimization; Transform coding; Enhanced DPCM; Hybrid GA-PSO; Image Compression; Lossless Compression; Remote Sensing (RS);

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communication Systems (ICSPCS), 2011 5th International Conference on

Conference_Location

Honolulu, HI

Print_ISBN

978-1-4577-1179-4

Electronic_ISBN

978-1-4577-1178-7

Type

conf

DOI

10.1109/ICSPCS.2011.6140839

Filename

6140839