Correlation based universal image/video coding loss recovery

Jinjian Wu, Weisi Lin*, Guangming Shi, Jimin Xiao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Coding artifacts are annoying in highly compressed signals. Most of the existing artifact reduction methods are designed for one specific type of artifacts, codecs, and bitrates, which are complex and exclusive for one type of artifact reduction. Since both the compressed image/video and the coding error contain information of the original signal, they are highly correlated. Therefore, we try to recover some lost data based on the correlation between the compressed signal and the coding error, and introduce a novel and universal artifact reduction method. Firstly, according to the spatial correlation among pixels, a pixel-adaptive anisotropic filter is designed to reconstruct the distorted signal. Next, a globally optimal filter is designed to further recover the coding loss. Experimental results demonstrate that within an extensive range of bitrates, the proposed method achieves about 0.8 dB, 0.45 dB, 0.3 dB, and 0.2 dB on average of PSNR improvement for JPEG, MPEG4, H.264/AVC, and HEVC compressed signals, respectively.

Original languageEnglish
Pages (from-to)1507-1515
Number of pages9
JournalJournal of Visual Communication and Image Representation
Issue number7
Publication statusPublished - Oct 2014
Externally publishedYes


  • Artifact reduction
  • Coding loss recovery
  • Correlation
  • Global optimization
  • Image/Video coding
  • Pixel-adaptive
  • Reconstruction
  • Structural self-similarity

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