Iterative backward segmentation for hierarchical wavelet image coding

We investigate a new class of scalable image coders. We target at the same time multiresolution (for spatial scalability) and hierarchical segmentation based decompositions (for object based scalability). Hierarchical segmentation allows to access the description of a scene in terms of regions or objects at several resolution levels, and thus encode and transmit the objects selectively. From a coding viewpoint, it is obviously interesting to couple the multi-level segmentation with a critically decimated decomposition of the image (to avoid redundancy of representation). We propose a new method to evaluate the hierarchical segmentation of an image using its wavelet decomposition. As the segmentation map is embedded by reconstruction inside the decomposition, we do not need to transmit it separately, thus reducing the bit rate. Simulations show that a prototype coder of this type is competitive with conventional image coders, while offering in addition new perspectives for object based coding and manipulations