Postprocessing of Compressed Images via Sequential Denoising

Yehuda Dar, Alfred M. Bruckstein, Michael Elad, Raja Giryes

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number7460139
Pages (from-to)3044-3058
Number of pages15
JournalIEEE Transactions on Image Processing
Volume25
Issue number7
DOIs
StatePublished - Jul 2016

Keywords

  • Deblocking
  • Denoising
  • Image Restoration
  • Lossy Compression
  • Plug-and-Play Prior
  • Postprocessing

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