IEICE TRANSACTIONS on Fundamentals
Deblocking Algorithm for Block-Based Coded Images Using Singularity Detection from Multiscale Edges
Summary :
The current paper presents an effective deblocking algorithm for block-based coded images using singularity detection in a wavelet transform. Blocking artifacts appear periodically at block boundaries in block-based coded images. The local maxima of a wavelet transform modulus detect all singularities, including blocking artifacts, from multiscale edges. Accordingly, the current study discriminates between a blocking artifact and an edge by estimating the Lipschitz regularity of the local maxima and removing the wavelet transform modulus of a blocking artifact that has a negative Lipschitz regularity exponent. Experimental results showed that the performance of the proposed algorithm was objectively and subjectively superior.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E86-A No.8 pp.2172-2178
- Publication Date
- 2003/08/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- LETTER
- Category
- Image
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Suk-Hwan LEE, Seong-Geun KWON, Kee-Koo KWON, Byung-Ju KIM, Jong-Won LEE, Kuhn-Il LEE, "Deblocking Algorithm for Block-Based Coded Images Using Singularity Detection from Multiscale Edges" in IEICE TRANSACTIONS on Fundamentals,
vol. E86-A, no. 8, pp. 2172-2178, August 2003, doi: .
Abstract: The current paper presents an effective deblocking algorithm for block-based coded images using singularity detection in a wavelet transform. Blocking artifacts appear periodically at block boundaries in block-based coded images. The local maxima of a wavelet transform modulus detect all singularities, including blocking artifacts, from multiscale edges. Accordingly, the current study discriminates between a blocking artifact and an edge by estimating the Lipschitz regularity of the local maxima and removing the wavelet transform modulus of a blocking artifact that has a negative Lipschitz regularity exponent. Experimental results showed that the performance of the proposed algorithm was objectively and subjectively superior.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e86-a_8_2172/_p
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@ARTICLE{e86-a_8_2172,
author={Suk-Hwan LEE, Seong-Geun KWON, Kee-Koo KWON, Byung-Ju KIM, Jong-Won LEE, Kuhn-Il LEE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Deblocking Algorithm for Block-Based Coded Images Using Singularity Detection from Multiscale Edges},
year={2003},
volume={E86-A},
number={8},
pages={2172-2178},
abstract={The current paper presents an effective deblocking algorithm for block-based coded images using singularity detection in a wavelet transform. Blocking artifacts appear periodically at block boundaries in block-based coded images. The local maxima of a wavelet transform modulus detect all singularities, including blocking artifacts, from multiscale edges. Accordingly, the current study discriminates between a blocking artifact and an edge by estimating the Lipschitz regularity of the local maxima and removing the wavelet transform modulus of a blocking artifact that has a negative Lipschitz regularity exponent. Experimental results showed that the performance of the proposed algorithm was objectively and subjectively superior.},
keywords={},
doi={},
ISSN={},
month={August},}
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TY - JOUR
TI - Deblocking Algorithm for Block-Based Coded Images Using Singularity Detection from Multiscale Edges
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2172
EP - 2178
AU - Suk-Hwan LEE
AU - Seong-Geun KWON
AU - Kee-Koo KWON
AU - Byung-Ju KIM
AU - Jong-Won LEE
AU - Kuhn-Il LEE
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E86-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2003
AB - The current paper presents an effective deblocking algorithm for block-based coded images using singularity detection in a wavelet transform. Blocking artifacts appear periodically at block boundaries in block-based coded images. The local maxima of a wavelet transform modulus detect all singularities, including blocking artifacts, from multiscale edges. Accordingly, the current study discriminates between a blocking artifact and an edge by estimating the Lipschitz regularity of the local maxima and removing the wavelet transform modulus of a blocking artifact that has a negative Lipschitz regularity exponent. Experimental results showed that the performance of the proposed algorithm was objectively and subjectively superior.
ER -
English
