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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xuanguo Wu Hong Shen |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Computer Science and Technology, University of Science and Technology of China, China (Xuanguo Wu; Hong Shen) |
| Abstract | Due to channel noise and congestion, video data packets can be lost during transmission in error-prone networks, which severely affects the quality of received video sequences. The conventional inter-frame error concealment (EC) methods estimate a motion vector (MV) for a corrupted block or reconstruct the corrupted pixel values using spatial and temporal weighted interpolation, which may result in boundary discontinuity and blurring artifacts of the reconstructed region. In this paper, we reconstruct corrupted macroblock (MB) by predicting sub-partitions and synthesizing the corrupted MB to reduce boundary discontinuity and avoid blurring artifacts. First, we select the optimal MV for each neighboring boundary using minimum side match distortion from a candidate MV set, and then we calculate the optimal cut path between the overlapping regions to synthesize the corrupted MB. The simulation results show that our proposed method is able to achieve significantly higher PSNR as well as better visual quality than using the H.264/AVC reference software. |
| Starting Page | 253 |
| Ending Page | 257 |
| File Size | 443181 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424465132 |
| e-ISBN | 9781424465163 |
| DOI | 10.1109/CISP.2010.5648292 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-16 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Visualization Image synthesis Video sequences Error concealment Graph cut Estimation Streaming media Automatic voltage control H.264/AVC Pixel Image reconstruction Side match distortion |
| Content Type | Text |
| Resource Type | Article |
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