An investigative study of multispectral lossy data compression using vector quantization

Abstract

Spectral vector quantization is presently applied to multispectral imagery from airborne scanners; the vector is here defined as an array of pixels from the same location from each channel. Attention is given to the effect of varying the size of the vector codebook on the quality of the compression and on subsequent classification. The rate of compression is programmable, but higher degradation is associated with higher compression ratios.