Embedded coding of palette images in the topological space

Summary form only given. Most existing image coding techniques resolve the uncertainty of an image source on a pixel-by-pixel basis. We demonstrate the effectiveness of region-based image models for the class of palette images. We propose to represent the index map of a palette image by a collection of successively refined color regions, from which the original index map can be reconstructed without any error. Within the framework of region-based modeling, we present a conditional coding approach to avoid information leakage during the multiple passes. Motivated by the distinguished characteristics of palette images, we propose to exploit topological property of isolated uniform-color regions while resolving the uncertainty of region boundaries. Our region-based image model not only provides an embedded representation of palette images in the topological space but also achieves excellent compression performance.