Overlapped adaptive partitioning for image coding based on the theory of iterated functions systems

Memoryless blockwise partitioning induces blockiness artifacts highly disturbing to the human visual system. This paper presents a new partitioning with overlapped blocks in the context of image coding based on iterated transformations systems. Each block of the partition is extended by n pixels. As usual each cell is expressed as the contractive transformation of another part of the image. During the decoding, values of pixels corresponding to overlapped regions are computed as the weighted sum of the different contributions leading to that pixel. This overlapped partitioning is embedded in a quadtree segmentation of the image support. In order to avoid blurring effects in small blocks while maintaining efficiency in bigger ones, the overlapping width n is a function of the block size. Simulations show a very significant improvement of the visual quality of decoded images with no increase of the bitrate request