Arithmetic coding for data compression
Communications of the ACM
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
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In image compression using wavelet transforms the final stage of processing often involves entropy encoding, out of which arithmetic coding is most essential. A significant contributor to the effectiveness of the arithmetic encoding is the selection of coding contexts. We show for various context selection schemes, that the interbit correlations in the multi-symbol alphabet is a primary source of compression gain in the entropy coding of the image. Further, we analyze the use of more conventional context selection schemes and show that full image histograms contain information not yet available to the decoder in embedded algorithms. The use of predictors in the embedded algorithm can be quite ineffective.