Lossless to Lossy Dual-Tree BEZW Compression for Hyperspectral Images

This paper proposes a lossless to lossy compression scheme for hyperspectral images based on dual-tree Binary Embedded Zerotree Wavelet (BEZW) algorithm. The algorithm adapts Karhunen-Loeve Transform and Discrete Wavelet Transform to achieve 3-D integer reversible hybrid transform and decorrelate spectral and spatial data. Since statistics of the hyperspectral image are not symmetrical, the asymmetrical dual-tree structure is introduced. The 3-D BEZW algorithm compresses hyperspectral images by implementing progressive bitplane coding. The lossless and lossy compression performance is compared with other state-of-the-art predictive coding and transform-based coding algorithms on Airborne Visible/Infrared Imaging Spectrometer images. Results show that the 3-D-BEZW lossless compression performance is comparable with the best predictive algorithms, while its computational cost is comparable with those of transform-based algorithms.