Statistic model for coding subband images using VQ and arithmetic coding

Andre Nicoulin; Marco Mattavelli

doi:10.1117/12.131484

1 November 1992 Statistic model for coding subband images using VQ and arithmetic coding

Andre Nicoulin, Marco Mattavelli

Proceedings Volume 1818, Visual Communications and Image Processing '92; (1992) https://doi.org/10.1117/12.131484
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

Abstract

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.

Citation Download Citation

Andre Nicoulin and Marco Mattavelli "Statistic model for coding subband images using VQ and arithmetic coding", Proc. SPIE 1818, Visual Communications and Image Processing '92, (1 November 1992); https://doi.org/10.1117/12.131484

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