Classification-based adaptive regularization for fast deblocking

Tae Yong Kim; Sang Kwang Lee; Joon-Ki Paik; Yo-Sung Ho

doi:10.1117/12.334720

28 December 1998 Classification-based adaptive regularization for fast deblocking

Tae Yong Kim, Sang Kwang Lee, Joon-Ki Paik, Yo-Sung Ho

Proceedings Volume 3653, Visual Communications and Image Processing '99; (1998) https://doi.org/10.1117/12.334720
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

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.

Citation Download Citation

Tae Yong Kim, Sang Kwang Lee, Joon-Ki Paik, and Yo-Sung Ho "Classification-based adaptive regularization for fast deblocking", Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); https://doi.org/10.1117/12.334720

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