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dc.contributor.authorHuang, Yu-Len
dc.contributor.authorLien, Hsiu-Yi
dc.date.accessioned2009-06-02T06:40:03Z
dc.date.accessioned2020-05-25T06:41:43Z-
dc.date.available2009-06-02T06:40:03Z
dc.date.available2020-05-25T06:41:43Z-
dc.date.issued2006-10-11T07:53:10Z
dc.date.submitted2004-12-15
dc.identifier.urihttp://dspace.lib.fcu.edu.tw/handle/2377/1007-
dc.description.abstractThe performance of MPEG video transmission over error-prone channels is limited by the channel noise. An efficient error concealment (EC) scheme is essential for diminishing the impact of transmission errors in a compressed video. A number of error concealment (EC) techniques have been developed to combat the transmission errors. However, the techniques are always inefficient when the motions of object in a video are fast or complex. In this paper, a novel adaptive EC algorithm is proposed to conceal the error for block-based image coding systems by using neural network (NN) techniques in the spatial domain. In the proposed algorithm, the self-organizing map (SOM) is used for estimating and reconstructing the motion vectors of damaged blocks. The SOM has a great capacity for visualizing and interpreting high-dimensional data sets. Computer simulation results show that the visual quality and the PSNR evaluation of reconstructed frames are significantly improved by using the proposed EC algorithm. From the experimental results, we find that the proposed algorithm is expected to be a useful EC algorithm for motion vector compressed video in error-prone networks.
dc.description.sponsorship大同大學,台北市  
dc.format.extent6p.
dc.format.extent1038892 bytes
dc.format.mimetypeapplication/pdf
dc.language.isozh_TW
dc.relation.ispartofseries2004 ICS會議
dc.subjectError concealment
dc.subjectneural network
dc.subjectSOM
dc.subjectmotion vector estimation
dc.subjectMPEG video
dc.subject.otherArtificial Intelligence
dc.titleTemporal Error Concealment Using Self-Organizing Map*
分類:2004年 ICS 國際計算機會議

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