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Browsing by Author "Mert, Yakup Murat"

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    Citation Count: Töreyin, Behçet Uğur; Yılmaz, Ozan; Mert, Yakup Murat. "Evaluation of on-board integer wavelet transform based spectral decorrelation schemes for lossless compression of hyperspectral images", 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Lausanne: Switzerland, 2014.
    Evaluation of on-board integer wavelet transform based spectral decorrelation schemes for lossless compression of hyperspectral images
    (2014) Töreyin, Behçet Uğur; Yılmaz, Ozan; Mert, Yakup Murat; 19325
    Integer-coefficient Discrete Wavelet Transformation (DWT) filters widely used in the literature are implemented and investigated as spectral decorrelator for on-board lossless hyperspectral image compression. 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 low computational complexity and high CR. Extensive 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. Results suggest that Cohen-DaubechiesFeauveau (CDF) 9/7 integer-coefficient wavelet transform with five levels of spectral subband decomposition would be an efficient spectral decorrelator for on-board lossless hyperspectral image compression.
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    Citation Count: Toreyin, Behcet Ugur...et al., "Lossless Hyperspectral Image Compression Using Wavelet Transform Based Spectral Decorrelation", 7th International Conference on Recent Advances in Space Technologies (RAST), pp. 250-253, (2015).
    Lossless Hyperspectral Image Compression Using Wavelet Transform Based Spectral Decorrelation
    (IEEE, 2015) Töreyin, Behçet Uğur; Yılmaz, Ozan; Mert, Yakup Murat; Türk, Fethi; 19325
    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 on-board lossless hyperspectral image compression.