A SEGMENTATION-BASED PREDICTIVE MULTIRESOLUTION IMAGE CODER

Recursive rectilinear tessellations like quadtree are widely used in i mage coding, but a regular tessellation, despite its simple geometry, may not suit image compression because it is too rigid to reflect the scene structure of an image. This paper presents a new image pyramid f ormed by adaptive, tree-structured segmentation to be a framework of a predictive multiresolution image coder. Subjectively appealing compre ssion results are obtained at different resolutions by scene-adaptive, tree-structured segmentation and by exploiting the statistical depend ency between the layers of the image pyramid. The adaptive segmentatio n-based image coder is constructed by recursive, least-squares piecewi se functional approximation. The seemingly expensive encoding process can be made efficient by an incremental least-squares computation tech nique. The decoding is simple and can be done in real time if assisted by existing hardware technology.