Efficient Lossless Compression of 4D Hyperspectral Image Data

Time-lapse hyperspectral imaging technology has been used for various remote sensing applications due to its excellent capability of monitoring regions of interest over a period of time. However, large data volume of fourdimensional hyperspectral imagery demands for massive data compression techniques. While conventional 3D hyperspectral data compression methods exploit only spatial and spectral correlations, we proposed a novel lossless compression algorithm that can achieve significant gains on compression efficiency by also taking into account temporal correlations inherent in the dataset. Experimental results demonstrated the effectiveness of the proposed algorithm.