Best Achievable Compression Ratio for Lossy Image Coding

The trade-o3 between image 4delity and coding rate is reached with several techniques, but all of them require an ability to measure distortion. The problem is that 4nding a general enough measure of perceptual quality has proven to be an elusive goal. Here, we propose a novel technique for deriving an optimal compression ratio for lossy coding based on the relationship between information theory and the problem of testing hypotheses. The best achievable compression ratio determines a boundary between achievable and non-achievable regions in the trade-o3 between source 4delity and coding rate. The resultant performance bound is operational in that it is directly achievable by a constructive procedure, as suggested in a theorem that states the relationship between the best achievable compression ratio and the Kullback–Leibler information gain. As an example of the proposed technique, we analyze the e3ects of lossy compression at the best achievable compression ratio on the identi4cation of breast cancer microcalci4cations. ? 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.