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Proceedings Paper

Classification-based adaptive regularization for fast deblocking
Author(s): Tae Yong Kim; Sang Kwang Lee; Joon-Ki Paik; Yo-Sung Ho
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Paper Abstract

In this paper we propose an iterative image restoration method using block edge classification for reducing block artifact in compressed images. In order to efficiently reduce block artifacts, a block is classified as edge or non-edge block, and the adaptive regularized iterative restoration method is used. The proposed restoration method is based on the observation that the quantization operation in a series of coding preprocess is a nonlinear and many-to-one mapping operator. And then we propose an adaptive iterative image restoration algorithm for removing the nonlinear and space- varying degradation. With some minor modifications the proposed image restoration method can be used for postprocessing reconstructed image sequences in HDTV, DVD, or video conferencing systems.

Paper Details

Date Published: 28 December 1998
PDF: 8 pages
Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); doi: 10.1117/12.334720
Show Author Affiliations
Tae Yong Kim, Chung-Ang Univ. (South Korea)
Sang Kwang Lee, Kwangju Institute of Science and Technology (South Korea)
Joon-Ki Paik, Chung-Ang Univ. (South Korea)
Yo-Sung Ho, Kwangju Institute of Science and Technology (South Korea)

Published in SPIE Proceedings Vol. 3653:
Visual Communications and Image Processing '99
Kiyoharu Aizawa; Robert L. Stevenson; Ya-Qin Zhang, Editor(s)

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