Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding
This paper proposes learning-based approaches for transcoding MPEG-2 video into HEVC. In the training mode of the transcoder, mappings between extracted features and split decisions are calculated. While in the transcoding mode, the split decisions of coding units of the HEVC video are predicted. Tw...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | article |
| منشور في: |
2020
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/11073/16658 |
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| _version_ | 1864513433552027648 |
|---|---|
| author | Shanableh, Tamer |
| author2 | Hassan, Mahitab Alaaeldin |
| author2_role | author |
| author_facet | Shanableh, Tamer Hassan, Mahitab Alaaeldin |
| author_role | author |
| dc.creator.none.fl_str_mv | Shanableh, Tamer Hassan, Mahitab Alaaeldin |
| dc.date.none.fl_str_mv | 2020-05-17T10:06:51Z 2020-05-17T10:06:51Z 2020 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | T. Shanableh and M. Hassan, "Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding," SN Applied Sciences, Springer, Accepted for publication, May, 2020 2523-3971 http://hdl.handle.net/11073/16658 |
| dc.language.none.fl_str_mv | en_US |
| dc.publisher.none.fl_str_mv | Springer |
| dc.relation.none.fl_str_mv | https://doi.org/10.1007/s42452-020-2909-7 |
| dc.subject.none.fl_str_mv | Video coding Video transcoding HEVC High Efficiency Video Coding (HEVC) Machine learning |
| dc.title.none.fl_str_mv | Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding |
| dc.type.none.fl_str_mv | Peer-Reviewed Preprint info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | This paper proposes learning-based approaches for transcoding MPEG-2 video into HEVC. In the training mode of the transcoder, mappings between extracted features and split decisions are calculated. While in the transcoding mode, the split decisions of coding units of the HEVC video are predicted. Two formulations are proposed for the prediction of split decisions based on multi model and multi-tier solutions. In the former solution, multi models are generated based on the total number of split flags in a coding unit. While in the latter solution, split decisions are modelled at three different coding depths. The proposed solutions are evaluated in terms of excessive bitrate, drop in PSNR, classification accuracy, model generation time and transcoding speedup. It is shown that the multi-tier solution maintains the rate-distortion behaviour of full re-encoding at the expense of lower gain in transcoding speedup. In comparison to existing work, it is shown that the proposed solutions offer a significant enhancement in terms of rate-distortion performance and classification accuracy. |
| format | article |
| id | aus_ef67ddf3f4c286f20e0d1887f86d3d00 |
| identifier_str_mv | T. Shanableh and M. Hassan, "Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding," SN Applied Sciences, Springer, Accepted for publication, May, 2020 2523-3971 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/16658 |
| publishDate | 2020 |
| publisher.none.fl_str_mv | Springer |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Predicting Split Decisions in MPEG-2 to HEVC Video TranscodingShanableh, TamerHassan, Mahitab AlaaeldinVideo codingVideo transcodingHEVCHigh Efficiency Video Coding (HEVC)Machine learningThis paper proposes learning-based approaches for transcoding MPEG-2 video into HEVC. In the training mode of the transcoder, mappings between extracted features and split decisions are calculated. While in the transcoding mode, the split decisions of coding units of the HEVC video are predicted. Two formulations are proposed for the prediction of split decisions based on multi model and multi-tier solutions. In the former solution, multi models are generated based on the total number of split flags in a coding unit. While in the latter solution, split decisions are modelled at three different coding depths. The proposed solutions are evaluated in terms of excessive bitrate, drop in PSNR, classification accuracy, model generation time and transcoding speedup. It is shown that the multi-tier solution maintains the rate-distortion behaviour of full re-encoding at the expense of lower gain in transcoding speedup. In comparison to existing work, it is shown that the proposed solutions offer a significant enhancement in terms of rate-distortion performance and classification accuracy.Springer2020-05-17T10:06:51Z2020-05-17T10:06:51Z2020Peer-ReviewedPreprintinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfT. Shanableh and M. Hassan, "Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding," SN Applied Sciences, Springer, Accepted for publication, May, 20202523-3971http://hdl.handle.net/11073/16658en_UShttps://doi.org/10.1007/s42452-020-2909-7oai:repository.aus.edu:11073/166582024-08-22T12:07:32Z |
| spellingShingle | Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding Shanableh, Tamer Video coding Video transcoding HEVC High Efficiency Video Coding (HEVC) Machine learning |
| status_str | publishedVersion |
| title | Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding |
| title_full | Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding |
| title_fullStr | Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding |
| title_full_unstemmed | Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding |
| title_short | Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding |
| title_sort | Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding |
| topic | Video coding Video transcoding HEVC High Efficiency Video Coding (HEVC) Machine learning |
| url | http://hdl.handle.net/11073/16658 |