2018 IEEE International Workshop on Signal Processing Systems (SiPS) 2018

DOI: 10.1109/sips.2018.8598306

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Performance and Computational Complexity of the Future Video Coding

Pierre-Loup Cabarat²,

Wassim Hamidouche³

et al.

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Cited by 4 publications

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Towards A Live Software Decoder Implementation For The Upcoming Versatile Video Coding (VVC) Codec

¹

,

²

,

³

et al. 2020

2020 IEEE International Conference on Image Processing (ICIP)

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Towards A Live Software Decoder Implementation For The Upcoming Versatile Video Coding (VVC) Codec

¹

,

²

,

³

et al. 2020

2020 IEEE International Conference on Image Processing (ICIP)

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No abstract

Compression Performance of the Versatile Video Coding: HD and UHD Visual Quality Monitoring

¹

,

²

,

³

et al. 2019

2019 Picture Coding Symposium (PCS)

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Video compression and content quality have become one of the most research topic in the recent years. Predominantly, trends obviously signpost that the video usage over the Internet is on the upsurge. Simultaneously, users' requirement for enlarged resolution and higher quality is rising. Consequently, a huge effort has been made for video coding technologies and quality monitoring. In this paper, we present a subjective-based comparison as well as an objective measurement between the newest Versatile Video Coding (VVC) and the well-known High Efficiency Video Coding (HEVC) standards. Several videos of various content are selected as tested sequences. Both High Definition (HD) and Ultra High Definition (UHD) resolutions are used in this experiment. An extensive range of bit-rates from low to high bit-rates were selected. These sequences are encoded using both HEVC reference software (HM-16.2) and the latest reference software of VVC (VTM-5.0). Obtained results have shown that VVC outperforms consistently HEVC, for realistic bit rates and quality levels, in the range of 40% on the subjective scale. For the objective measurements, using PSNR, SSIM and VMAF as quality metrics, the quality enhancement of VVC over HEVC is ranging from 31% to 40%, depending on video content and spatial resolution.

Network Resource Allocation for Industry 4.0 With Delay and Safety Constraints

Sardar,

Rao,

Alpcan

et al. 2024

IEEE Trans. Cogn. Commun. Netw.

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No abstract

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