Statistic model for coding subband images using VQ and arithmetic coding
A. Nicoulin, Marco Mattavelli · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
A new entropy coding algorithm for the compression of subband images is presented. By combining vector quantization (VQ) and scalar quantization (SQ) with entropy coding, the proposed scheme exploits the remaining statistical dependencies among the subband samples, and keeps an optimal control on local distortion by scalar quantization. The system is based on a statistical model which uses VQ information to generate low entropy probability tables for an arithmetic coder. The bit rate can be shared between VQ-rate and SQ-rate, allowing many possible configurations in terms of performances and implementation complexity. The proposed system shows improved performances when compared with other existing methods.