Integer-coefficient Discrete Wavelet Transformation (DWT) filters widely used in the literature are implemented and investigated as spectral decorrelator. As the performance of spectral decorrelation step has direct impact on the compression ratio (CR), it is important to employ the most convenient spectral decorrelator in terms of computational complexity and CR. Tests using AVIRIS image data set are carried out and CRs corresponding to various subband decomposition levels are presented within a lossless hyperspectral compression framework. Two-dimensional images corresponding to each band is compressed using JPEG-LS algorithm. Results suggest that Cohen-Daubechies-Feauveau (CDF) 9/7 integer-coefficient wavelet transform with five levels of spectral subband decomposition would be an efficient spectral decorrelator for onboard lossless hyperspectral image compression.


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    Title :

    Lossless hyperspectral image compression using wavelet transform based spectral decorrelation


    Contributors:


    Publication date :

    2015-06-01


    Size :

    706953 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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