DocumentCode :
3148279
Title :
A novel error concealment approach based on general regression neural network
Author :
Shao, Shih-Chun ; Chen, Jun-Horng
Author_Institution :
Grad. Inst. of Autom. Technol., Nat. Taipei Univ. of Technol., Taipei, Taiwan
fYear :
2011
fDate :
16-18 April 2011
Firstpage :
4679
Lastpage :
4682
Abstract :
In video communication, packet is inevitably lost or transmitted erroneously over error-prone channel. If there are packets lost, the entire video quality will be degraded. The error concealment is thus proposed to solve this problem effectively. Therefore, this paper will propose the general regression neural network (GRNN) can be used to estimate the motion vectors of the corrupted macroblocks. The proposed approach can restore corrupted frame effectively. Experimental results show that the proposed approach in this work can improve the defect of conventional approach and raise the average PSNR of the recovered video sequence.
Keywords :
image matching; image sequences; motion estimation; neural nets; telecommunication computing; video communication; video signal processing; error concealment approach; general regression neural network; macroblock motion vector estimation; video communication; video sequence; Artificial neural networks; Biological neural networks; Conferences; Joints; PSNR; Training; Video sequences; error concealment; general regression neural network; video communication;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on
Conference_Location :
XianNing
Print_ISBN :
978-1-61284-458-9
Type :
conf
DOI :
10.1109/CECNET.2011.5768232
Filename :
5768232
Link To Document :
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