Predictive graph construction for image compression

In this work, we propose a new method of graph construction for graph-based image compression. In particular, because of the overhead incurred by graph transmission to the receiver, we focus our attention to develop an efficient method to con- struct and to code the graph representation of the image. The proposed method employs innovative edge metrics, quantization and prediction techniques, leading to a compact yet high-quality graph, corresponding to a very efficient transform that performs very well on natural as well as piece-wise smooth images. We have tested our method on different images and, compared to the standard DCT, it provides an average quality gain of 1.6 dB.