H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial Regression
This paper introduces two polynomial regression solutions for error concealment by predicting the values of motion vectors of lost macroblocks. The two solutions are online and offline polynomial regression modeling. In the former solution, the regression model is built during the decoding process w...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | article |
| منشور في: |
2015
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/11073/8827 |
| الوسوم: |
إضافة وسم
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| _version_ | 1864513434971799552 |
|---|---|
| author | Shanableh, Tamer |
| author2 | Assaleh, Khaled |
| author2_role | author |
| author_facet | Shanableh, Tamer Assaleh, Khaled |
| author_role | author |
| dc.creator.none.fl_str_mv | Shanableh, Tamer Assaleh, Khaled |
| dc.date.none.fl_str_mv | 2015 2017-05-04T04:43:43Z 2017-05-04T04:43:43Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | Shanableh, T. & Assaleh, K. (2015). H.264/AVC motion vector concealment solutions using online and offline polynomial regression. Signal, Image and Video Processing, 9(3), 581-588. doi:10.1007/s11760-013-0489-3 1863-1711 http://hdl.handle.net/11073/8827 10.1007/s11760-013-0489-3 |
| dc.language.none.fl_str_mv | en_US |
| dc.publisher.none.fl_str_mv | Springer |
| dc.relation.none.fl_str_mv | http://doi.org/10.1007/s11760-013-0489-3 |
| dc.subject.none.fl_str_mv | Video compression Error concealment Machine learning Regression |
| dc.title.none.fl_str_mv | H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial Regression |
| dc.type.none.fl_str_mv | Postprint Peer-Reviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | This paper introduces two polynomial regression solutions for error concealment by predicting the values of motion vectors of lost macroblocks. The two solutions are online and offline polynomial regression modeling. In the former solution, the regression model is built during the decoding process whilst in the latter solution; the model is built during the encoding or the transcoding process and then used at the decoder for concealment. Both solutions make use of the spatially and temporally neighboring motion vectors for building the regression models. The advantages and disadvantages of the proposed solutions are elaborated upon. In comparison to existing work, the experimental results show that the proposed solutions have clear advantages of computational time requirements and motion vector prediction accuracy. |
| format | article |
| id | aus_5ecfbcd7125ffa4de232a6cce3c89303 |
| identifier_str_mv | Shanableh, T. & Assaleh, K. (2015). H.264/AVC motion vector concealment solutions using online and offline polynomial regression. Signal, Image and Video Processing, 9(3), 581-588. doi:10.1007/s11760-013-0489-3 1863-1711 10.1007/s11760-013-0489-3 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/8827 |
| publishDate | 2015 |
| publisher.none.fl_str_mv | Springer |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial RegressionShanableh, TamerAssaleh, KhaledVideo compressionError concealmentMachine learningRegressionThis paper introduces two polynomial regression solutions for error concealment by predicting the values of motion vectors of lost macroblocks. The two solutions are online and offline polynomial regression modeling. In the former solution, the regression model is built during the decoding process whilst in the latter solution; the model is built during the encoding or the transcoding process and then used at the decoder for concealment. Both solutions make use of the spatially and temporally neighboring motion vectors for building the regression models. The advantages and disadvantages of the proposed solutions are elaborated upon. In comparison to existing work, the experimental results show that the proposed solutions have clear advantages of computational time requirements and motion vector prediction accuracy.Springer2017-05-04T04:43:43Z2017-05-04T04:43:43Z2015PostprintPeer-Reviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfShanableh, T. & Assaleh, K. (2015). H.264/AVC motion vector concealment solutions using online and offline polynomial regression. Signal, Image and Video Processing, 9(3), 581-588. doi:10.1007/s11760-013-0489-31863-1711http://hdl.handle.net/11073/882710.1007/s11760-013-0489-3en_UShttp://doi.org/10.1007/s11760-013-0489-3oai:repository.aus.edu:11073/88272024-08-22T12:08:50Z |
| spellingShingle | H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial Regression Shanableh, Tamer Video compression Error concealment Machine learning Regression |
| status_str | publishedVersion |
| title | H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial Regression |
| title_full | H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial Regression |
| title_fullStr | H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial Regression |
| title_full_unstemmed | H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial Regression |
| title_short | H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial Regression |
| title_sort | H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial Regression |
| topic | Video compression Error concealment Machine learning Regression |
| url | http://hdl.handle.net/11073/8827 |