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Post-Processing for JPEG-Coded Image Deblocking via Sparse Representation and Adaptive Residual Threshold
  • KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Post-Processing for JPEG-Coded Image Deblocking via Sparse Representation and Adaptive Residual Threshold


Abstract

The problem of blocking artifacts is very common in block-based image and video compression, especially at very low bit rates. In this paper, we propose a post-processing method for JPEG-coded image deblocking via sparse representation and adaptive residual threshold. This method includes three steps. First, we obtain the dictionary by online dictionary learning and the compressed images. The dictionary is then modified by the histogram of oriented gradient (HOG) feature descriptor and K-means cluster. Second, an adaptive residual threshold for orthogonal matching pursuit (OMP) is proposed and used for sparse coding by combining blind image blocking assessment. At last, to take advantage of human visual system (HVS), the edge regions of the obtained deblocked image can be further modified by the edge regions of the compressed image. The experimental results show that our proposed method can keep the image more texture and edge information while reducing the image blocking artifacts.


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Cite this article

[IEEE Style]
L. Wang, X. Zhou, C. Wang and B. Jiang, "Post-Processing for JPEG-Coded Image Deblocking via Sparse Representation and Adaptive Residual Threshold," KSII Transactions on Internet and Information Systems, vol. 11, no. 3, pp. 1700-1721, 2017. DOI: 10.3837/tiis.2017.03.025.

[ACM Style]
Liping Wang, Xiao Zhou, Chengyou Wang, and Baochen Jiang. 2017. Post-Processing for JPEG-Coded Image Deblocking via Sparse Representation and Adaptive Residual Threshold. KSII Transactions on Internet and Information Systems, 11, 3, (2017), 1700-1721. DOI: 10.3837/tiis.2017.03.025.