A Study of High Frame Rate Video Formats

Mackin, Alex; Zhang, Fan; Bull, David

doi:10.1109/tmm.2018.2880603

Cited by 64 publications

(50 citation statements)

References 65 publications

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“…The performance of the proposed method for all tested sequences is summarised in Table I, where original VTM 4.01 is used as a benchmark 2 . It is noted that the overall bit rate saving according to PSNR (for luma components only) is 3.76% for low QP range (22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37), which is higher than those for JVET-N0254 and JVET-O0059, and this improvement is evident for all tested video classes (resolutions). When VMAF is employed for quality assessment, the average BD-rates are similar to those for PSNR, at -4.85% for high QP range and -3.40% low QP range.…”

Section: A Compression Performancementioning

confidence: 88%

“…It can be also observed that, for the high QP range (27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42), the average coding gains are slightly higher than those for low QP range, and this difference is emphasised when VMAF is used for quality assessment. Rate-PSNR and rate-VMAF curves for four selected test sequences at various spatial resolutions, DaylightRoad2, RitualDance, PartyScene and BQMall., are plotted in Fig.…”

Section: A Compression Performancementioning

confidence: 96%

“…One hundred and eight source video sequences were used to train the employed CNN, selected from publicly available databases, including BVI-HFR [30], BVI-Texture [31], Harmonic 4K [32] and Netflix Chimera [33]. All were 10 bit, 3940×2160, 60 frames per second, YCbCr 4:2:0, raw video clips.…”

Section: B Training Contentmentioning

confidence: 99%

See 2 more Smart Citations

Enhancing VVC Through Cnn-Based Post-Processing

Zhang

Feng

Bull

2020

2020 IEEE International Conference on Multimedia and Expo (ICME)

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This paper presents a new Convolutional Neural Network (CNN) based post-processing approach for video compression, which is applied at the decoder to improve the reconstruction quality. This method has been integrated with the Versatile Video Coding Test Model (VTM) 4.01, and evaluated using the Random Access (RA) configuration using the Joint Video Exploration Team (JVET) Common Test Conditions (CTC). The results show coding gains on all tested sequences at various spatial resolutions over different quantisation parameter ranges, with average bit rate savings (based on Bjøntegaard Delta measurements) of 3.90% and 4.13%, when PSNR and VMAF are used as quality metrics respectively. The computational complexities of different CNN architecture variants have also been investigated.

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Section: A Compression Performancementioning

confidence: 88%

Section: A Compression Performancementioning

confidence: 96%

See 1 more Smart Citation

Enhancing VVC Through Cnn-Based Post-Processing

Zhang

Feng

Bull

2020

2020 IEEE International Conference on Multimedia and Expo (ICME)

Self Cite

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“…Winkler [37] quantifies the characteristics of the contents in existing image and video datasets, including spatial information and colorfulness for color images, and motion vectors for video contents, based on which the representativeness of a set of contents can be evaluated [38], [39]. In [40], it is suggested to consider attributes of the test material such as brightness, colorfulness, amount of motion, scene cuts, types of the content, etc.…”

Section: Content Characterizationmentioning

confidence: 99%

Wide Color Gamut Image Content Characterization: Method, Evaluation, and Applications

Lee

Vigier

Callet

et al. 2021

IEEE Trans. Multimedia

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In this paper, we propose a novel framework to characterize a wide color gamut image content based on perceived quality due to the processes that change color gamut, and demonstrate two practical use cases where the framework can be applied. We first introduce the main framework and implementation details. Then, we provide analysis for understanding of existing wide color gamut datasets with quantitative characterization criteria on their characteristics, where four criteria, i.e., coverage, total coverage, uniformity, and total uniformity, are proposed. Finally, the framework is applied to content selection in a gamut mapping evaluation scenario in order to enhance reliability and robustness of the evaluation results. As a result, the framework fulfils content characterization for studies where quality of experience of wide color gamut stimuli is involved.Index Terms-Wide color gamut, color gamut mapping, content characterization, content selection, quality of experience.

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“…This has lead to its incorporation in recent data compression standards and its use in many different cases [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19]. In addition, ANS-based encoders could be applicable to a very wide range of multimedia scenarios, such as an alternative to the Rice-Golomb codes employed in the energy-efficient scheme described in [20], as a high-throughput entropy encoder in a high frame rate video format [21], or in general as an entropy encoder in schemes for sparse coding [22], learned image compression [23], compressive sensing [24], or point cloud data compression [25]. In [26], ANS is employed to code large-alphabets sources.…”

Section: Introductionmentioning

confidence: 99%

Redundancy and Optimization of tANS Entropy Encoders

Blanes¹,

Hernández-Cabronero²,

Serra-Sagristà³

et al. 2021

IEEE Trans. Multimedia

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Nowadays entropy encoders are part of almost all data compression methods, with the Asymmetrical Numeral Systems (ANS) family of entropy encoders having recently risen in popularity. Entropy encoders based on the tabled variant of ANS are known to provide varying performances depending on their internal design. In this paper, we present a method that calculates encoder redundancies in almost linear time, which translates in practice to thousand-fold speedups in redundancy calculations for small automatons, and allows redundancy calculations for automatons with tens of millions of states that would be otherwise prohibitive. We also address the problem of improving tabled ANS encoder designs, by employing the aforementioned redundancy calculation method in conjunction with a stochastic hill climbing strategy. The proposed approach consistently outperforms state-of-the-art methods in tabled ANS encoder design. For automatons of twice the alphabet size, experimental results show redundancy reductions around 10% over the default initialization method and over 30% for random initialization.

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A Study of High Frame Rate Video Formats

Cited by 64 publications

References 65 publications

Enhancing VVC Through Cnn-Based Post-Processing

Enhancing VVC Through Cnn-Based Post-Processing

Wide Color Gamut Image Content Characterization: Method, Evaluation, and Applications

Redundancy and Optimization of tANS Entropy Encoders

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