A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters
The famous video coding standards of this era, such as high efficiency video coding (HEVC) and H.264/AVC, offer numerous coding parameters to enhance the compression ratio. These standards exploited a robust rate-distortion optimization (RDO) methodology to select the appropriate macroblock (MB) cod...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8318583/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832582404107141120 |
|---|---|
| author | Muhammad Asif Maaz Bin Ahmad Imtiaz A. Taj Muhammad Tahir |
| author_facet | Muhammad Asif Maaz Bin Ahmad Imtiaz A. Taj Muhammad Tahir |
| author_sort | Muhammad Asif |
| collection | DOAJ |
| description | The famous video coding standards of this era, such as high efficiency video coding (HEVC) and H.264/AVC, offer numerous coding parameters to enhance the compression ratio. These standards exploited a robust rate-distortion optimization (RDO) methodology to select the appropriate macroblock (MB) coding parameters, such as prediction type, modes, and block sizes. The exploitation of the RDO technique contributes significantly to increase the computational complexity of the coding process. In this paper, a generalized multi-layer framework is presented, which provides a hierarchical optimized way to select MB prediction parameters. Each layer of the proposed framework incorporates multiple innovative algorithms to shortlist the candidate prediction parameters prior to the RDO process. Moreover, in order to select the suitable prediction type and block size for intra-prediction, two techniques are proposed. The presented framework is flexible enough to accommodate various mode selection techniques that make it excellent choice to be used in the modern coding standards. The experimental results show that coding time is reduced up to 74% without significant loss in visual video. |
| format | Article |
| id | doaj-art-c4657c570abb4f55aa62e52b34cc4fa5 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-c4657c570abb4f55aa62e52b34cc4fa52025-01-30T00:00:31ZengIEEEIEEE Access2169-35362018-01-016252772529110.1109/ACCESS.2018.28168528318583A Generalized Multi-Layer Framework for Video Coding to Select Prediction ParametersMuhammad Asif0https://orcid.org/0000-0001-6811-0044Maaz Bin Ahmad1Imtiaz A. Taj2Muhammad Tahir3Department of Electrical Engineering, Capital University of Science and Technology, Islamabad, PakistanCollege of Computing and Information Sciences Department, PAF Karachi Institute of Economics and Technology, Karachi, PakistanDepartment of Electrical Engineering, Capital University of Science and Technology, Islamabad, PakistanDepartment of Electrical Engineering, Capital University of Science and Technology, Islamabad, PakistanThe famous video coding standards of this era, such as high efficiency video coding (HEVC) and H.264/AVC, offer numerous coding parameters to enhance the compression ratio. These standards exploited a robust rate-distortion optimization (RDO) methodology to select the appropriate macroblock (MB) coding parameters, such as prediction type, modes, and block sizes. The exploitation of the RDO technique contributes significantly to increase the computational complexity of the coding process. In this paper, a generalized multi-layer framework is presented, which provides a hierarchical optimized way to select MB prediction parameters. Each layer of the proposed framework incorporates multiple innovative algorithms to shortlist the candidate prediction parameters prior to the RDO process. Moreover, in order to select the suitable prediction type and block size for intra-prediction, two techniques are proposed. The presented framework is flexible enough to accommodate various mode selection techniques that make it excellent choice to be used in the modern coding standards. The experimental results show that coding time is reduced up to 74% without significant loss in visual video.https://ieeexplore.ieee.org/document/8318583/RDOintra-predictioninter-predictionH.264/AVCHEVCvideo coding |
| spellingShingle | Muhammad Asif Maaz Bin Ahmad Imtiaz A. Taj Muhammad Tahir A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters IEEE Access RDO intra-prediction inter-prediction H.264/AVC HEVC video coding |
| title | A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters |
| title_full | A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters |
| title_fullStr | A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters |
| title_full_unstemmed | A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters |
| title_short | A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters |
| title_sort | generalized multi layer framework for video coding to select prediction parameters |
| topic | RDO intra-prediction inter-prediction H.264/AVC HEVC video coding |
| url | https://ieeexplore.ieee.org/document/8318583/ |
| work_keys_str_mv | AT muhammadasif ageneralizedmultilayerframeworkforvideocodingtoselectpredictionparameters AT maazbinahmad ageneralizedmultilayerframeworkforvideocodingtoselectpredictionparameters AT imtiazataj ageneralizedmultilayerframeworkforvideocodingtoselectpredictionparameters AT muhammadtahir ageneralizedmultilayerframeworkforvideocodingtoselectpredictionparameters AT muhammadasif generalizedmultilayerframeworkforvideocodingtoselectpredictionparameters AT maazbinahmad generalizedmultilayerframeworkforvideocodingtoselectpredictionparameters AT imtiazataj generalizedmultilayerframeworkforvideocodingtoselectpredictionparameters AT muhammadtahir generalizedmultilayerframeworkforvideocodingtoselectpredictionparameters |