Embedded Coding of Palette Images in the Topological Space (Summary)

Most existing image coding techniques resolve the uncertainty of an image source on a pixel-by-pixel basis. In this paper, 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. Among ten images in our corpus, our topological coder outperforms PWC [1] for six images and offers slightly worse performance than PWC for the other four. For some images containing abundant uniform-color regions, the bit savings are as much as 30-40%.