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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8318583/ |
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| Summary: | 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. |
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| ISSN: | 2169-3536 |