Significance of pre-processing and its impact on lossless hyperspectral image compression

The primitive aspect of hyperspectral imagery is its inherent spatial and spectral correlation. This correlation is exploited by subjecting the imaging cube to compression. A new approach to accomplish lossless hyperspectral image compression has been proposed. The imaging cube is subjected to pre-processing stage prior to entropy coding. Pre-processing stage comprises band normalization, ordering of bands followed by image scanning. A new sorting technique entitled Greedy Heap Sorting is suggested. The proposed strategy yields an average compression ratio (CR) of 4.93 and average bits per pixel (bpp) of 3.08. The proficiency of the system is on par with the existing contemporary algorithms for lossless hyperspectral image compression in terms of CR, bpp and reduced complexity.