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
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;
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on
Conference_Location :
XianNing
Print_ISBN :
978-1-61284-458-9
DOI :
10.1109/CECNET.2011.5768232