Mr. Mohamed Abdelazim Profile

Mohamed Abdelazim

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Proceedings Article | 20 June 2021 Presentation + Paper

HEVC improved performance with end-to-end super resolution

Mohamed Abdelazim, Ahmed Hamza, Abdelrahman Abdelazim, Djamel Ait-Boudaoud

Proceedings Volume 11788, 117880M (2021) https://doi.org/10.1117/12.2589651

KEYWORDS: Video, Computer programming, Video coding, Super resolution, Neural networks, Quantization, Video processing, Associative arrays, Standards development, Lawrencium

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High Efficiency Video Coding (HEVC), also known as H.265 and MPEG-H part2 is the state of art video encoder standard developed by the Joint Collaborative Team on Video Coding (JCT-VC). It achieves up to 50% better data compression at the same level of video quality than its predecessor (H.264-AVC). One of the main challenges of the HEVC coding is its overall performance as the improved quality and bit rate of the standard coding comes with significant performance overhead. This motivates significant research to reduce the overall complexity. In this paper, we explore the effect of applying down sampling and up sampling of coded video on the performance of the HEVC. The down sampling is applied to all video frames before the encoder process begins and the up sampling is applied to all the video frames after the decoding process is completed. We use an average filter in down sampling, and machine learning based network (SRCNN) for the up sampling. In contrast to other methods, the down sampling and up sampling are applied on frame level outside the encoding/decoding processes and not in block level. Our experiments show the down sampling and up sampling can improve the HEVC encoding/decoding performance by up to 50% in some sequences with limited impact on the output encoded bit rate and decoded video quality. The performance comparison is done using different quantization values.

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