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

Ghamisi, P ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/ICSPCS.2011.6140839
  3. Abstract:
  4. 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
  5. Keywords:
  6. Remote Sensing (RS) ; Compression methods ; Enhanced DPCM ; Hybrid GA-PSO ; Hyperspectral Data ; JPEG 2000 ; JPEG standards ; Lossless ; Lossless compression ; Storage spaces ; Test case ; Transmission systems ; Communication systems ; Compression ratio (machinery) ; Digital image storage ; Image compression ; Remote sensing ; Signal processing ; Genetic algorithms
  7. Source: 5th International Conference on Signal Processing and Telecommunication Systems, ICSPCS'2011, Honolulu, HI, 12 December 2011 through 14 December 2011 ; 2011 ; 9781457711800 (ISBN)
  8. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6140839