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Postprocessing of Compressed Images via Sequential Denoising

机译:通过顺序降噪对压缩图像进行后处理

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摘要

In this paper, 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, 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. In particular, we demonstrate impressive gains in image quality for several leading compression methods—JPEG, JPEG2000, and HEVC.
机译:在本文中,我们提出了一种用于压缩伪像减少的新型后处理技术。我们的方法基于将这项任务视为一个反问题,并利用现有的最新图像去噪算法进行正则化。我们依靠最近提出的即插即用先验框架,通过乘数的交替方向方法提出一般逆问题的解决方案,从而导致一系列高斯去噪步骤。我们方案的关键特征是压缩-减压过程的线性化,以便获得可以优化的配方。此外,我们提供了几种基本压缩程序的线性近似分析。所提出的方法适用于依赖变换编码的各种压缩技术。特别是,我们展示了几种领先的压缩方法(JPEG,JPEG2000和HEVC)在图像质量方面的令人瞩目的成就。

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