The use of low-bit depth approaches for band ordering in hyperspectral image compression

Hyperspectral imaging is a popular research topic and it has wide range of application areas. Despite all the advantages, because its huge amount of data, compression is required. In some compression methods, performing a band-ordering as a preprocessing step increases compression performance. In this paper, 1-bit transform (1BT), two-bit transform (2BT), constrained 1-bit transform (C-1BT) and weighted constrained 1-bit transform (WC-1BT) based low bit-depth band-ordering approaches are proposed to reduce the computational complexity of band ordering methods. Performances of the proposed approaches are evaluated in five different hyperspectral images and experimental results are investigated.