title: Progressive vector quantization on a massively parallel SIMD machine with application to multispectral image data.
abstract: This correspondence discusses a progressive vector quantization (VQ) compression approach, which decomposes image data into a number of levels using full-search VQ. The final level is losslessly compressed, enabling lossless reconstruction. The computational difficulties are addressed by implementation on a massively parallel SIMD machine. We demonstrate progressive VQ on multispectral imagery obtained from the advanced very high resolution radiometer (AVHRR) and other earth-observation image data, and investigate the tradeoffs in selecting the number of decomposition levels and codebook training method.
authors.affiliation: Dept. of Comput. Sci., Bowie State Univ., MD.
authors.forename: M
authors.initials: M
authors.lastname: Manohar
authors.forename: J C
authors.initials: JC
authors.lastname: Tilton