Self-learning-based post-processing for image/video deblocking via sparse representation

Chia Hung Yeh, Li Wei Kang*, Yi Wen Chiou, Chia Wen Lin, Shu Jhen Fan Jiang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

40 Citations (Scopus)


Blocking artifact, characterized by visually noticeable changes in pixel values along block boundaries, is a common problem in block-based image/video compression, especially at low bitrate coding. Various post-processing techniques have been proposed to reduce blocking artifacts, but they usually introduce excessive blurring or ringing effects. This paper proposes a self-learning-based post-processing framework for image/video deblocking by properly formulating deblocking as an MCA (morphological component analysis)-based image decomposition problem via sparse representation. Without the need of any prior knowledge (e.g., the positions where blocking artifacts occur, the algorithm used for compression, or the characteristics of image to be processed) about the blocking artifacts to be removed, the proposed framework can automatically learn two dictionaries for decomposing an input decoded image into its "blocking component" and "non-blocking component." More specifically, the proposed method first decomposes a frame into the low-frequency and high-frequency parts by applying BM3D (block-matching and 3D filtering) algorithm. The high-frequency part is then decomposed into a blocking component and a non-blocking component by performing dictionary learning and sparse coding based on MCA. As a result, the blocking component can be removed from the image/video frame successfully while preserving most original visual details. Experimental results demonstrate the efficacy of the proposed algorithm.

Original languageEnglish
Pages (from-to)891-903
Number of pages13
JournalJournal of Visual Communication and Image Representation
Issue number5
Publication statusPublished - 2014 Jul
Externally publishedYes


  • Blocking artifact
  • Deblocking
  • Dictionary learning
  • Image/video enhancement
  • Image/video restoration
  • Morphological component analysis
  • Post-processing
  • Sparse representation

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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