Institute for Data Analysis and Visualization

Image coding requires an effective representation of images to provide dimensionality reduction, a quantization strategy to maintain image quality, and finally the error free encoding of quantized coefficients. In the coding of quantized coefficients, Huffman coding and arithmetic coding have been used most commonly and are suggested as alternatives in the JPEG standard. In some recent work, zerotree coding has been proposed as an alternate method, that considers the dependence of of quantized coefficients from subband to subband, and thus appears as a generalization of the context-based approach often used with arithmetic coding. In this paper, we propose to review these approaches and discuss them as special cases of an analysis based approach to the coding of coefficients. The requirements on causality and computational complexity implied by arithmetic and zero-tree coding will be studied and other schemes proposed for the choice of the predictive coefficient contexts that are suggested by image analysis.