A Unified Video Codec for SDR, HDR, and 360° Video Applications

Xiu, Xiaoyu; Hanhart, Philippe; He, Ying; Ye, Yan; Vanam, Rahul; Lu, Taoran; Pu, Fangjun; Yin, Peng

doi:10.1109/tcsvt.2019.2945698

Cited by 10 publications

(7 citation statements)

References 7 publications

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“…The VTM software encoder implements two algorithms to estimate LMCS parameters for HDR PQ videos and SDR/HDR HLG videos, respectively. For HDR PQ videos, the algorithm is designed to optimize for weighted PSNR (wPSNR), the luma mapping curve being derived directly based on the weights used in wPSNR [53], [54]. For SDR/HDR HLG, the algorithm is designed to optimize for PSNR.…”

Section: Lmcs Encoder Parameters Estimationmentioning

confidence: 99%

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VVC In-Loop Filters

Karczewicz

Taquet

et al. 2021

IEEE Trans. Circuits Syst. Video Technol.

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This paper presents an overview of the technologies for in-loop processing and filtering in the Versatile Video Coding (VVC) standard. These processes comprise luma mapping with chroma scaling, deblocking filter, sample adaptive offset, adaptive loop filter and cross-component adaptive loop filter. They are qualified as "in-loop" because they are applied inside the encoding and decoding loops, before storing the pictures in the decoded picture buffer. The filters are complementary and address different purposes. Luma mapping with chroma scaling aims at adaptively modifying the coded samples distribution for improved coding efficiency. The deblocking filter aims at reducing blocking discontinuities. Sample adaptive offset mostly aims at reducing artifacts resulting from the quantization of transform coefficients. Adaptive loop filter and cross-component adaptive loop filter are adaptive filters enabling to enhance the reconstructed signal, using for instance Wiener-filter encoding approaches. The paper provides an overview of the in-loop filtering process and a detailed description of the filtering algorithms. Objective compression efficiency results are provided for each filter, with indication of cumulative coding gains. Subjective benefits are illustrated. Implementation issues considered during the design of the VVC in-loop filters are also discussed.

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Section: Lmcs Encoder Parameters Estimationmentioning

confidence: 99%

“…To show subjective improvement, LMCS is configured to use an adaptive curve. The design is based on [53], where a parametric model estimates the subjective importance of each piece of the piecewise linear model and pre-defines codeword allocation for luma intervals based on piece importance. Fig.…”

Section: F Lmcs Performancementioning

confidence: 99%

VVC In-Loop Filters

Karczewicz

Taquet

et al. 2021

IEEE Trans. Circuits Syst. Video Technol.

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“…Multi-type tree (MTT) structures as were already proposed for the JEM have been used in most CfP responses [4], [12]- [16], [18]- [21]. The MTT (or QTBTTT) is a combination of a quadtree (QT) with nested binary trees (BT) as proposed for the JEM in [22] and triple-/ ternary trees (TT).…”

Section: A Multi-type Treementioning

confidence: 99%

“…Further limitations are set to the maximum depth of the BT and TT. Proponents who measured the coding gain impact of MTT partitioning separately from other novel coding tools reported luma BD-rate changes of −3.26% [12], −2.3% [13], −2.36% [14] and −1.95% [15] in a tool-on test against JEM-7.0 using QTBT for the RA configuration.…”

Section: A Multi-type Treementioning

confidence: 99%

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General Video Coding Technology in Responses to the Joint Call for Proposals on Video Compression With Capability Beyond HEVC

Bross

Andersson

Blaser

et al. 2020

IEEE Trans. Circuits Syst. Video Technol.

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After the development of the High-Efficiency Video Coding Standard (HEVC), ITU-T VCEG and ISO/IEC MPEG formed the Joint Video Exploration Team (JVET), which started exploring video coding technology with higher coding efficiency, including development of a Joint Exploration Model (JEM) algorithm and a corresponding software implementation. The technology explored in the last version of the JEM further increases the compression capabilities of the hybrid video coding approach by adding new tools, reaching up to 30% bit rate reduction compared to HEVC based on the Bjøntegaard delta bit rate (BD-rate) metric, and further improvement beyond that in terms of subjective visual quality. This provided enough evidence to issue a joint Call for Proposals (CfP) for a new standardization activity now known as Versatile Video Coding (VVC). All technology proposed in the responses to the CfP was based on the classic block-based hybrid video coding design, extending it by new elements of partitioning, intra-and inter-picture prediction, prediction signal filtering, transforms, quantization/scaling, entropy coding, and in-loop filtering. This article provides an overview of technology that was proposed in the responses to the CfP, with a focus on techniques that were not already explored in the JEM context.

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Modern Video Coding Standards: H.264, H.265, and H.266

Drew

Liu

2021

Texts in Computer Science

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A Unified Video Codec for SDR, HDR, and 360° Video Applications

Cited by 10 publications

References 7 publications

VVC In-Loop Filters

VVC In-Loop Filters

General Video Coding Technology in Responses to the Joint Call for Proposals on Video Compression With Capability Beyond HEVC

Modern Video Coding Standards: H.264, H.265, and H.266

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