In this work, we investigate a new class of scalable image coders. We target at the same time multiresolution (for spatial scalability), critical (for compression efficiency) 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). However, the association of object representation combined with critically sampled multiresolution decomposition has not been studied to our knowledge. In this paper, we propose new methods to perform hierarchical segmentation of an image using critically decimated non linear filter banks; the resulting decomposition embeds a hierarchical segmentation map and is therefore particularly well suited for region based coding and progressive transmission. As the segmentation map is embedded by reconstruction inside the decomposition, we do not really need to transmit it separately, thus attempting to reduce the bitrate. Simulations show that a prototype coder of this type has a degradation in terms of rate/distortion tradeoff compared to a conventional wavelet based image coder, but offers in addition new perspectives for object based manipulations, coding and transmission.