Optimized decoding of JPEG images based on generalized graph Laplacians

摘要

We address the problem of optimizing the decoding of JPEG-compressed images, employing an approach based on the “generalized” graph Laplacian, a higher-order generalization of the usual graph Laplacian. The optimal decoding problem is formulated as a non-smooth but convex problem over a graph, and solved via the alternating directions method of multipliers. While similar, graph-based optimized decoding techniques exist, the use of our generalized graph Laplacian enables better recovery of the original smooth image from the transform coefficients, especially those coded at low bit-rates. Experimental results highlight the performance of our proposed approach in terms of reconstructed distortion and visual quality. Comparisons with the method based on the usual graph Laplacian and other state-of-the-art methods are also given.