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An Adaptive De-Blocking Algorithm Based on MRF
Hong Kong, China November 14-November 16
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICTAI.2005.3117th IEEE International Conference on ...
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Shengli Xie, Zhiliang Xu, "An Adaptive De-Blocking Algorithm Based on MRF," Tools with Artificial Intelligence, IEEE International Conference on, pp. 710-711, 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05), 2005.
 
 
BibTex
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@article{ 10.1109/ICTAI.2005.31,
author = {Shengli Xie and Zhiliang Xu},
title = {An Adaptive De-Blocking Algorithm Based on MRF},
journal ={Tools with Artificial Intelligence, IEEE International Conference on},
volume = {0},
year = {2005},
issn = {1082-3409},
pages = {710-711},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICTAI.2005.31},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Tools with Artificial Intelligence, IEEE International Conference on
TI - An Adaptive De-Blocking Algorithm Based on MRF
SN - 1082-3409
SP710
EP711
A1 - Shengli Xie,
A1 - Zhiliang Xu,
PY - 2005
KW - null
VL - 0
JA - Tools with Artificial Intelligence, IEEE International Conference on
ER -
 
Shengli Xie, South China University of Technology
Zhiliang Xu, South China University of Technology and Jiang Xi Normal University
One of the major drawbacks in block-based discrete cosine transform (BDCT) is the blocking artifacts at low bit rates. In this paper, an adaptive de-blocking algorithm based on Markov Random Field (MRF) is proposed. A visibility function of blocking artifacts is introduced which based on human visual system (HVS), together with edge information to construct a new adaptive potential function of MRF. The experiment results show that the proposed algorithm reduces the blocking artifacts effectively and preserves the original edges faithful.
Citation:
Shengli Xie, Zhiliang Xu, "An Adaptive De-Blocking Algorithm Based on MRF," ictai, pp.710-711, 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05), 2005
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