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Progressive vector quantization on a massively parallel SIMD machine with application to multispectral image data

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2 Author(s)
Manohar, M. ; Dept. of Comput. Sci., Bowie State Univ., MD, USA ; Tilton, J.C.

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

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Image Processing, IEEE Transactions on  (Volume:5 ,  Issue: 1 )