Packet Video Error Concealment With Auto Regressive Model
Packet Video Error Concealment With Auto Regressive Model
复制标题
使用自回归模型的分组视频错误隐藏
DOI：
10.1109/tcsvt.2011.2130450
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发表时间：
2012
影响因子：
8.4
通讯作者：
Zhao, Debin
中科院分区：
文献类型：
--
作者：
Ma, Siwe;Gao, Wen;Xiang, Xinguang;Zhang, Yongbing;Zhao, Debin
In this paper, auto regressive (AR) model is applied to error concealment for block-based packet video coding. In the proposed error concealment scheme, the motion vector for each corrupted block is first derived by any kind of recovery algorithms. Then each pixel within the corrupted block is replenished as the weighted summation of pixels within a square centered at the pixel indicated by the derived motion vector in a regression manner. Two block-dependent AR coefficient derivation algorithms under spatial and temporal continuity constraints are proposed respectively. The first one derives the AR coefficients via minimizing the summation of the weighted square errors within all the available neighboring blocks under the spatial continuity constraint. The confidence weight of each pixel sample within the available neighboring blocks is inversely proportional to the distance between the sample and the corrupted block. The second one derives the AR coefficients by minimizing the summation of the weighted square errors within an extended block in the previous frame along the motion trajectory under the temporal continuity constraint. The confidence weight of each extended sample is inversely proportional to the distance toward the corresponding motion aligned block whereas the confidence weight of each sample within the motion aligned block is set to be one. The regression results generated by the two algorithms are then merged to form the ultimate restorations. Various experimental results demonstrate that the proposed error concealment strategy is able to improve both the objective and subjective quality of the replenished blocks compared to other methods.
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DOI：
10.1109/tcsvt.2003.815168
发表时间：
2003-07
期刊：
IEEE Trans. Circuits Syst. Video Technol.
影响因子：
--
作者：
T. Wiegand;H. Schwarz;Anthony Joch;F. Kossentini;G. Sullivan
通讯作者：
T. Wiegand;H. Schwarz;Anthony Joch;F. Kossentini;G. Sullivan
DOI：
10.1109/79.855913
发表时间：
2000-07
期刊：
IEEE Signal Process. Mag.
影响因子：
--
作者：
Yao Wang;S. Wenger;Jiantao Wen;A. Katsaggelos
通讯作者：
Yao Wang;S. Wenger;Jiantao Wen;A. Katsaggelos
影响因子：
16.4
作者：
P. Salama;N. Shroff;E. Delp
通讯作者：
P. Salama;N. Shroff;E. Delp
DOI：
--
发表时间：
1998
期刊：
--
影响因子：
--
作者：
Kaoru Watanabe
通讯作者：
Kaoru Watanabe
DOI：
10.1109/76.728413
发表时间：
1998-10
期刊：
IEEE Trans. Circuits Syst. Video Technol.
影响因子：
--
作者：
Wenwu Zhu;Yao Wang;Qin-Fan Zhu
通讯作者：
Wenwu Zhu;Yao Wang;Qin-Fan Zhu