Title :
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
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);
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
DOI :
10.1109/ICSPCS.2011.6140839