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Résolution Spatio-temporelle Adaptative pour un Codage à Faible Complexité des Formats Vidéo Émergents

Abstract : The definition of the latest Ultra-High Definition TV (UHDTV) standard aims to increase the user’s quality of experience by introducing new video signal features such as 4K and High Frame-Rate (HFR). However, these new features multiply by a factor 8 the amount of data to be processed before transmission to the end user.In addition to this new format, broadcasters and Over-The-Top (OTT) content providers have to encode videos in different formats and at different bitrates due to the wide variety of devices with heterogeneous video format and network capacities used by consumers.SHVC, the scalable extension of the latest video coding standard High Efficiency Video Coding (HEVC) is a promising solution to address these issues but its computationally demanding architecture reaches its limit with the encoding and decoding of the data-heavy newly introduced immersive video features of the UHDTV video format.The objective of this thesis is thus to investigate lightweight scalable encoding approaches based on the adaptation of the spatio-temporal resolution. The first part of this document proposes two pre-processing tools, respectively using polyphase and wavelet frame-based approaches, to achieve spatial scalability with a slight complexity overhead.Then, the second part of this thesis addresses the design of a more conventional dual-layer scalable architecture using an HEVC encoder in the Base Layer (BL) for backward compatibility and a proposed low-complexity encoder, based on the local adaptation of the spatial resolution, for the Enhancement Layer (EL).Finally, the last part of this thesis investigates spatiotemporal resolution adaptation. A variable frame-rate algorithm is first proposed as pre-processing. This solution has been designed to locally and dynamically detect the lowest frame-rate that does not introduce visible motion artifacts. The proposed variable frame-rate and adaptive spatial resolution algorithms are then combined to offer a lightweight scalable coding of 4K HFR video contents.
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Submitted on : Friday, February 5, 2021 - 11:20:12 AM
Last modification on : Sunday, May 22, 2022 - 3:22:48 AM
Long-term archiving on: : Thursday, May 6, 2021 - 6:38:24 PM


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  • HAL Id : tel-03132567, version 1


Glenn Herrou. Résolution Spatio-temporelle Adaptative pour un Codage à Faible Complexité des Formats Vidéo Émergents. Traitement du signal et de l'image [eess.SP]. INSA de Rennes, 2019. Français. ⟨NNT : 2019ISAR0020⟩. ⟨tel-03132567⟩



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