In this work we propose a novel postprocessing technique for compression-artifact reduction. Our approach is based on posing this task as an inverse problem, with a regularization that leverages on existing state-of-the-art image denoising algorithms. We rely on the recently proposed Plug-and-Play Prior framework, suggesting the solution of general inverse problems via Alternating Direction Method of Multipliers (ADMM), leading to a sequence of Gaussian denoising steps. A key feature in our scheme is a linearization of the compression-decompression process, so as to get a formulation that can be optimized. In addition, we supply a thorough analysis of this linear approximation for several basic compression procedures. The proposed method is suitable for diverse compression techniques that rely on transform coding. Specifically, we demonstrate impressive gains in image quality for several leading compression methods - JPEG, JPEG2000, and HEVC.

本文提出了一种新的压缩伪影降低的后处理技术，该方法利用图像去噪算法作为正则化项，通过ADMM求解广义逆问题，进而获得高质量的压缩图像。该方法适用于各种基于变换编码的压缩技术，如JPEG，JPEG2000和HEVC等。

通过顺序去噪处理压缩图像