Compression of hyperspectral images with 2D wavelet transform using adjacent information and SPIHT slgorithm

In this paper, we propose compression algorithms for hyperspectral images based on the wavelet transform using adjacent band information. In the proposed algorithm, we divide the spectral bands into a number of groups. Then, within each group, we select a representative spectral band which has highest correlations with the remaining spectral bands within the group. The representative image is compressed using the 2-dimensional SPIHT algorithm. A characteristic of the SPIHT algorithm is that it provides information on significant coefficients of transformed images, which have large energies. We explore this characteristic and use the information to encode adjacent band images of the representative image.