A Fast Intra Mode Decision Based on Accuracy of Rate Distortion Model for AV1 Intra Encoding

Jeong, Jinwoo; Gankhuyag, Ganzorig; Kim, Yonghwan

doi:10.1109/itc-cscc.2019.8793367

Cited by 7 publications

(7 citation statements)

References 4 publications

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“…As presented at the Introduction, the related works [8]- [12] also developed solutions focusing at the AV1 intraframe encoding, but only works [11] and [12] are focused on Fig. 2.…”

Section: Results and Comparisonsmentioning

confidence: 99%

“…There are a few works in the literature presenting efficient solutions targeting the AV1 intra-frame prediction, like [8]- [12]. The work [8] focus on the AV1 intra-frame prediction coding efficiency improvement.…”

Section: Introductionmentioning

confidence: 99%

“…The works [9] and [10] focused on hardware-based solutions. The works [11] and [12] are focused on computational effort reduction for the AV1 intra-frame prediction, using heuristics. Then, none of these works explore machine learning based solutions.…”

Section: Introductionmentioning

confidence: 99%

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GM-RF: An AV1 Intra-Frame Fast Decision Based on Random Forest

Rosa

Palomino

Porto

et al. 2022

2022 IEEE International Conference on Image Processing (ICIP)

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This paper presents the Grouping of Modes based on Random Forest (GM-RF), a fast decision algorithm for the AOMedia Video 1 (AV1) intra-frame prediction applying machine learning (ML). AV1 implements a wide variety of intra-frame prediction tools, significantly increasing the required computational effort. The GM-RF uses trained Random Forest (RF) models to reduce the number of intra-frame prediction modes evaluated for each encoded block. Experimental results show that the GM-RF achieves an average time savings of 50.19%, with a BD-BR of 7.41%. Compared with related works, GM-RF reached time savings from 5.6 to 10 times higher at a cost of a higher BDBR. To the best of the authors' knowledge, this is the first solution in the literature using ML to reduce the AV1 intra-frame prediction computational effort.

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“…As presented at the Introduction, the related works [8]- [12] also developed solutions focusing at the AV1 intraframe encoding, but only works [11] and [12] are focused on Fig. 2.…”

Section: Results and Comparisonsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

GM-RF: An AV1 Intra-Frame Fast Decision Based on Random Forest

Rosa

Palomino

Porto

et al. 2022

2022 IEEE International Conference on Image Processing (ICIP)

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“…Considering the AV1 intra prediction, two works can be found in the literature. In Jeong et al [41], the authors use the variation and Welford's online method with the RDO calculations made by the reference software to choose the best intra mode. In Jeong et al [42], the authors propose the analysis of the intra prediction mode of the luma channel to include or not some intra prediction mode candidates for chroma channels, applied on HD or higher resolutions.…”

Section: A Algorithmic Optimization For Av1mentioning

confidence: 99%

AV1 and VVC Video Codecs: Overview on Complexity Reduction and Hardware Design

Corrêa

Saldanha

Borges

et al. 2021

IEEE Open J. Circuits Syst.

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This article presents an extensive review of the state-of-the-art system-level solutions featuring complexity reduction and/or dedicated hardware designs for the AV1 and VVC video coding formats. These formats introduced several novel coding techniques compared to their predecessors to improve the coding efficiency at the cost of a significant computational cost. In this article, we discuss the main novelties of AV1 and VVC in each coding module, including block partitioning, intra and inter prediction, transform, entropy coding, and in-loop filters. Then, we present the main published works focusing on complexity reduction and hardware designs for AV1 and VVC. Most of the complexity reduction solutions target the complex and flexible block partitioning structures of these encoders to provide a better tradeoff between coding efficiency and complexity reduction whereas the hardware designs focus on the challenge of implementing the new coding tools to attend real-time processing of high-definition videos. Even with the presented works reaching impressive results, these research fields remain opened for innovative contributions, as discussed in this article.

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“…A fast inter prediction algorithm using decision tree is proposed in [31] to selectively decide a reduced set of inter modes to subject to rate-distortion (RD) test so that the AV1 encoding time is reduced. AV1 intra mode decision is also accelerated in [32] with adaptive early termination. Moreover, a machine learning based fast AV1 encoder is also studied in [33].…”

Section: Introductionmentioning

confidence: 99%

User-Priority Based AV1 Coding Tool Selection

2021

IEEE Trans. on Broadcast.

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AV1 is an open-source video coding technique developed by Alliance for Open Media (AOMedia). Many powerful coding tools introduced to AV1 has made its encoding time significantly increased. In this paper, we aim at simplifying the AV1 encoder by facilitating selection of some coding tools depending on users' specific application preference. We firstly design a coding tool OFF-test to evaluate coding performance of intra, inter, and in-loop filter coding tools in AV1 encoder in order to define a criterion to evaluate the importance of each coding tool by measuring the Bjøntegaard delta bit rate (BDBR) loss and time saving (TS) when each coding tool is turned OFF. Furthermore, the importance of each coding tool is analyzed based on the predefined criterion. Lastly, we suggest two intra coding tool selection methods, three inter coding tool selection methods, and three overall coding tool selection methods to simplify AV1 encoder based on users' preference of qualitypriority or low-complexity-priority. Experimental results show that our proposed low-complexity-priority selection method saves 30.72% of encoding time with only 0.91% loss in BDBR sense, and the quality-priority selection method saves 4.64% of encoding time with 0.02% BDBR loss.

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A Fast Intra Mode Decision Based on Accuracy of Rate Distortion Model for AV1 Intra Encoding

Cited by 7 publications

References 4 publications

GM-RF: An AV1 Intra-Frame Fast Decision Based on Random Forest

GM-RF: An AV1 Intra-Frame Fast Decision Based on Random Forest

AV1 and VVC Video Codecs: Overview on Complexity Reduction and Hardware Design

User-Priority Based AV1 Coding Tool Selection

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