Statistical inference for a stochastic multiresolution image decomposition scheme

The stochastic pyramid transform is a multiresolution structure that decomposes a random signal into a collection of random detail signals on a pyramid. The detail signals have a significantly simpler structure. It is however difficult to analytically calculate their probability distribution. In this paper, we propose a (vector quantization based) statistical inference technique that fits the detail signals to given data. An explicit dependence structure is introduced between each level of the pyramid and the coarse level immediately above it. The potential of this approach is illustrated with a simple example