Asymmetric Dct-Jnd for Luminance Adaptation Effects: an Application To Perceptual Video Coding in Mv-Hevc

Jaballah, Sami; Larabi, Mohamed–Chaker; Tahar, Jamel Belhadj

doi:10.1109/icassp.2018.8461738

Cited by 7 publications

(3 citation statements)

References 17 publications

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“…When these stimuli present simultaneously, the presence of one stimulus weakens or enhances the response to other excitations, called visual masking effects. The masking effects can be categorized as Luminance Masking (LM), spatial and temporal contrast masking [42], binocular masking [35,119] and pattern masking [93] depending on the input stimulus. The response of strongest stimuli will weaken the rest of visual responses.…”

Section: Temporal Contrast Sensitivitymentioning

confidence: 99%

“…Visual sensitivity refers to the visual response to input visual signals, which affected by many factors including spatial contrast [4,5,7,32], temporal contrast [33,45,67], input stimuli pattern [93], brightness [44,81], color sensitivity [61,71], type of visual cells, fovea and eccentricities [13], binocular masking [35] and so on. Barten's CSF [4] built the spatial CSF as an isotropic band-pass shaped function of image size, luminance level, and pupil size, where the sensitivity 𝑆 (𝑢) is calculated as [4]…”

Section: Visual Sensitivity Modelsmentioning

confidence: 99%

“…Kim et al [42] modelled the visual sensitivity by jointly exploiting temporal masking from motion vector, contrast masking from edge, luminance masking from mean pixel values in images. Furthermore, the visual sensitivity in stereo vision was modelled by considering the binocular masking in [35].…”

Section: Visual Sensitivity Modelsmentioning

confidence: 99%

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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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