Abstract:

A hyperspectral image compression algorithm with dimension segmentation quantization on each vector is introduced. The algorithm adopts dimension segmentation to divide vector into several parts and designs each part of the codebook based on the nature of Hadamard transformation. Optimal vector quantizer design principle is used in the designing process. Combined with a stepbystep exclude inequality algorithm and LBG (Linda Bazo Gray) clustering algorithm, the final codebook can be quickly generated. The whole codebook performance can be improved by designing each part of the codebook to achieve optimal performance in Hadamard domain. Experimental results show that the algorithm is superior to other algorithms in image recovery quality and complexity at the same codebook size.