Artifact reduction in low bit rate DCT-based image compression

Jiebo Luo; Chang Wen Chen; Kevin J. Parker; Thomas S. Huang

doi:10.1109/83.535848

Artifact reduction in low bit rate DCT-based image compression

Jiebo Luo
, Chang Wen Chen
, Kevin J. Parker
, Thomas S. Huang

Department of Computer Science and Engineering

University of Rochester
University of Illinois at Urbana-Champaign

Research output: Contribution to journal › Article › peer-review

81 Scopus citations

Abstract

This correspondence presents a scheme for artifact reduction of low bit rate discrete-cosine-transform-compressed (DCT-compressed) images. First, the DC coefficients are calibrated using gradient continuity constraints. Then, an improved Huber-Markov-random-field-based (HMRF-based) smoothing is applied. The constrained optimization is implemented by the iterative conditional mode (ICM). Final reconstructions of typical images with improvements in both visual quality and peak signal-to-noise ratio (PSNR) are also shown.

Original language	English
Pages (from-to)	1363-1368
Number of pages	6
Journal	IEEE Transactions on Image Processing
Volume	5
Issue number	9
DOIs	https://doi.org/10.1109/83.535848
State	Published - 1996

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abstract = "This correspondence presents a scheme for artifact reduction of low bit rate discrete-cosine-transform-compressed (DCT-compressed) images. First, the DC coefficients are calibrated using gradient continuity constraints. Then, an improved Huber-Markov-random-field-based (HMRF-based) smoothing is applied. The constrained optimization is implemented by the iterative conditional mode (ICM). Final reconstructions of typical images with improvements in both visual quality and peak signal-to-noise ratio (PSNR) are also shown.",

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AB - This correspondence presents a scheme for artifact reduction of low bit rate discrete-cosine-transform-compressed (DCT-compressed) images. First, the DC coefficients are calibrated using gradient continuity constraints. Then, an improved Huber-Markov-random-field-based (HMRF-based) smoothing is applied. The constrained optimization is implemented by the iterative conditional mode (ICM). Final reconstructions of typical images with improvements in both visual quality and peak signal-to-noise ratio (PSNR) are also shown.

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Artifact reduction in low bit rate DCT-based image compression

Abstract

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