Digital image compression based on non-stationary and inhomogeneous multiresolution analyses

Adaptive wavelet-based image compression methods are introduced. In contrast to the classical wavelet decomposition scheme one can use different wavelet and scaling functions at every scale-this leads to nonstationary multiresolution analysis. An inhomogeneous multiresolution analysis is obtained by using different functions for the two directions in the tensor product of the bidimensional multiresolution analysis, furthermore these two methods are combined. The freedom in using different functions is exploited for image compression in an adaptive way. Special non-stationary and/or inhomogeneous multiresolution analysis is built out of the functions in a given library that is best suited for compression of a given image. This is done by minimizing cost-functions at every scale-level