Image coding based on a morphological representation of wavelet data

In this paper, an experimental study of the statistical properties of wavel et coefficients of image data is presented, as well as the design of two di fferent morphology-based image coding algorithms that make use of these sta tistics. A salient feature of the proposed methods is that, by a simple cha nge of quantizers, the same basic algorithm yields high performance embedde d or fixed rate coders. Another important feature is that the shape informa tion of morphological sets used in this coder is encoded implicitly by the values of wavelet coefficients, thus avoiding the use of explicit and rate expensive shape descriptors. These proposed algorithms, while achieving nea rly the same objective performance of state-of-the-art zerotree based metho ds, are able to produce reconstructions of a somewhat superior perceptual q uality, due to a property of joint compression and noise reduction they exh ibit.