Spatiotemporal Perception Aware Quantization Algorithm For Video Coding

Yan, Yunyao; Xiang, Guoqing; Li, Yuan; Xie, Xiaodong; Yan, Wei; Bao, Yungang

doi:10.1109/icme46284.2020.9102882

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…Based on the JND suppression, 𝑄𝑃 was enlarged to encode the residue if the distortion was within the JND range [96], which improved the compression ratio while maintaining the same visual quality. Meanwhile, spatial and temporal masking effects [96,99] were jointly considered in JND modelling and 𝑄𝑃 adaptation. Kim et al [42] proposed a novel transform domain JND and applied it to transform, quantization and RDO to exploit visual redundancies from JND.…”

Section: Perceptually Optimized Transform and Quantizationmentioning

confidence: 99%

A Survey on Perceptually Optimized Video Coding

Zhang¹,

Zhu²,

Jiang³

et al. 2021

Preprint

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Videos are developing in the trends of Ultra High Definition (UHD), High Frame Rate (HFR), High Dynamic Range (HDR), Wide Color Gammut (WCG) and high fidelity, which provide users with more realistic visual experiences. However, the amount of video data increases exponentially and requires high efficiency video compression for storage and network transmission. Perceptually optimized video coding aims to exploit visual redundancies in videos so as to maximize compression efficiency. In this paper, we present a systematic survey on the recent advances and challenges on perceptually optimized video coding. Firstly, we present problem formulation and framework of perceptually optimized video coding, which includes visual perception modelling, visual quality assessment and perception guided coding optimization. Secondly, the recent advances on visual factors, key computational visual models and quality assessment models are presented. Thirdly, we do systematic review on perceptual video coding optimizations from four key aspects, which includes perceptually optimized bit allocation, rate-distortion optimization, transform and quantization, filtering and enhancement. In each part, problem formulation, working flow, recent advances, advantages and challenges are presented. Fourthly, perceptual coding performance of latest coding standards and tools are experimentally analyzed. Finally, challenging issues and future opportunities on perceptual video coding are identified.CCS Concepts: • Computing methodologies → Image compression.

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Section: Perceptually Optimized Transform and Quantizationmentioning

confidence: 99%

A Survey on Perceptually Optimized Video Coding

Zhang¹,

Zhu²,

Jiang³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

A survey on just noticeable distortion estimation and its applications in video coding

Wang,

et al. 2024

Journal of Visual Communication and Image Representation

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A Survey on Perceptually Optimized Video Coding

et al. 2023

View full text Add to dashboard Cite

To provide users with more realistic visual experiences, videos are developing in the trends of Ultra High Definition (UHD), High Frame Rate (HFR), High Dynamic Range (HDR), Wide Color Gammut (WCG) and high clarity. However, the data amount of videos increases exponentially, which requires high efficiency video compression for storage and network transmission. Perceptually optimized video coding aims to maximize compression efficiency by exploiting visual redundancies. In this paper, we present a broad and systematic survey on perceptually optimized video coding. Firstly, we present problem formulation and framework of the perceptually optimized video coding, which includes visual perception modelling, visual quality assessment and perceptual video coding optimization. Secondly, recent advances on visual factors, computational perceptual models and quality assessment models are presented. Thirdly, we review perceptual video coding optimizations from four key aspects, including perceptually optimized bit allocation, rate-distortion optimization, transform and quantization, filtering and enhancement. In each part, problem formulation, working flow, recent advances, advantages and challenges are presented. Fourthly, perceptual coding performances of the latest coding standards and tools are experimentally analyzed. Finally, challenging issues and future opportunities are identified.

show abstract

Spatiotemporal Perception Aware Quantization Algorithm For Video Coding

Cited by 3 publications

References 9 publications

A Survey on Perceptually Optimized Video Coding

A Survey on Perceptually Optimized Video Coding

A survey on just noticeable distortion estimation and its applications in video coding

A Survey on Perceptually Optimized Video Coding

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