Graph-based Dequantization of Block-Compressed Piecewise Smooth Images

—Block-based image or video coding standards (e.g. JPEG) compress an image lossily by quantizing transform coefficients of non-overlapping pixel blocks. If the chosen quantization parameters (QP) are large, then hard decoding of a compressed image—using indexed quantization bin centers as reconstructed transform coefficients—can lead to unpleasant blocking artifacts. Leveraging on recent advances in graph signal processing (GSP), we propose a dequantization scheme specifically for piecewise smooth (PWS) images: images with sharp object boundaries and smooth interior surfaces. We first mathematically define a PWS image as a low-frequency signal with respect to an inter-pixel similarity graph with edges of weights 1 or 0. Using quantization bin boundaries as constraints, we then jointly optimize the desired graph-signal and the similarity graph in a unified framework. A generalization to consider generalized piecewise smooth (GPWS) images—where sharp object boundaries are r...

• Type: Journal
• Year: 2016
• Where: SPL
• Authors: Wei Hu, Gene Cheung, Masato Kazui
• Keywords: SPL 2016