Image compression using non-stationary and inhomogeneous multiresolution analyses

摘要

New methods for lossy image compression based on wavelet theory are introduced. Unlike the classical wavelet decomposition scheme, it is possible to have different scaling and wavelet filters at every scale by using non-stationary multiresolution analyses. For the bidimensional case, inhomogeneous multiresolution analyses using different wavelet filters for the two variables are introduced. Beyond it, these two methods are combined. All this freedom is used for compact image coding. The idea is to build out of the filters in a library that special non-stationary and/or inhomogeneous multiresolution analysis, that is best suited for a given image in the context of compact coding (in the sense of optimizing certain cost-functions). To identify the optimal filter combination, an adaptive algorithm of low complexity is developed. The usefulness of these new schemes for image compression is demonstrated.