Lossless hyper-spectral image compression based on XCJRCT, discrete wavelet transform and set partitioning in hierarchical trees coding

This paper proposed a new algorithm using invertible matrix transformation XCJRCT to eliminate the spectral redundancy, as well as combining with lifting scheme discrete wavelet transform (DWT) and set partitioning in hierarchical trees (SPIHT) coding. The experiment results show that the capabilities of lossless image compression are far better than JPEG-LS, WinZip, ARJ, and DPCM. With Canal test image (Band Sequential) of Jet Propulsion Laboratory (JPL) as an example data set, the average compression ratio increases about 43.09%, 38.17%, 36.08% 31.08% respectively compared with the above algorithms.