Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)
- 2002.07c
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- Pages.1424-1427
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- 2002
Adaptive Postprocessing Algorithm for Reduction of Blocking Artifacts Using Wavelet Transform and NNF
- Kwon, Kee-Koo (School of Electrical Engineering and Computer Science, Kyungpook National University) ;
- Park, Kyung-Nam (School of Electrical Engineering and Computer Science, Kyungpook National University) ;
- Kim, Byung-Ju (School of Electrical Engineering and Computer Science, Kyungpook National University) ;
- Lee, Suk-Hwan (School of Electrical Engineering and Computer Science, Kyungpook National University) ;
- Kwon, Seong-Geun (School of Electrical Engineering and Computer Science, Kyungpook National University) ;
- Lee, Kuhn-Il (School of Electrical Engineering and Computer Science, Kyungpook National University)
- Published : 2002.07.01
Abstract
This paper proposes a novel postprocessing algorithm for reducing the blocking artifacts in low bit rate block-based transform coded images, that use adaptive neural network filter (NNF) in wavelet transform domain. n this algorithm, after performing a 2-level wavelet transform of the decompressed image, the existence of locking artifacts is determined using statistical characteristic of neighborhood blocks. And then a different one-dimensional (1-D) or 2-D NNF is used to reduce the locking artifacts according to the classified regions. That is, for HL and LH subbands regions with the blocking artifacts, a different 1-D NNF is used. And 2-D NNF is used in HH subband. Experimental results show that the proposed algorithm produced better results than those of conventional algorithms both subjectively and objectively.
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