Parallel implementation of linear prediction model for lossless compression of hyperspectral airborne visible infrared imaging spectrometer images

Jarno S. Mielikäinen; Pekka J. Toivanen

doi:10.1117/1.1867998

1 January 2005 Parallel implementation of linear prediction model for lossless compression of hyperspectral airborne visible infrared imaging spectrometer images

Jarno S. Mielikäinen; Pekka J. Toivanen

Author Affiliations +

J. of Electronic Imaging, 14(1), 013010 (2005). doi:10.1117/1.1867998

Abstract

We present the implementation of a lossless hyperspectral image compression method for novel parallel environments. The method is an interband version of a linear prediction approach for hyperspectral images. The interband linear prediction method consists of two stages: predictive decorrelation that produces residuals and the entropy coding of the residuals. The compression part is embarrassingly parallel, while the decompression part uses pipelining to parallelize the method. The results and comparisons with other methods are discussed. The speedup of the thread version is almost linear with respect to the number of processors.

Citation Download Citation

Jarno S. Mielikäinen, Pekka J. Toivanen, "Parallel implementation of linear prediction model for lossless compression of hyperspectral airborne visible infrared imaging spectrometer images," Journal of Electronic Imaging 14(1), 013010 (1 January 2005). https://doi.org/10.1117/1.1867998

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