Progress and Opportunities in Modelling Just-Noticeable Difference (JND) for Multimedia

被引:21
作者
Lin, Weisi [1 ]
Ghinea, Gheorghita [2 ]
机构
[1] Nanyang Technol Univ, Dept Sch Comp Sci & Engn, Singapore 639798, Singapore
[2] Brunel Univ London, Dept Comp Sci, Uxbridge UB8 3PH, Middx, England
关键词
Visualization; Solid modeling; Computational modeling; Data models; Psychology; Brain modeling; Multimedia systems; JND model; multimedia; human visual system; human perception; brain functioning; machine learning; VIDEO QUALITY; VISUAL-ATTENTION; DISTORTION; CONTRAST; PERSONALITY; PERCEPTION; MASKING; DISCRIMINATION; DATASET; PROFILE;
D O I
10.1109/TMM.2021.3106503
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Just-Noticeable Difference (JND) is the minimal amount of signal change that the human being is able to perceive. The human has five major sensing organs, namely, eyes, ears, nose, skin and tongue, and therefore JND exists for the corresponding five signal modalities and their derivatives. JND can play an important role in many multimedia applications and services, because these imperfect human perceptual characteristics may be turned into advantages for relevant system design, development and optimization. This paper starts off by giving a general description for JND concepts and the related statistical processes. Then, existing computational models for visual JND, which represent the majority of the related research so far, are to be reviewed systematically, with both handcrafted modeling and machine learning approaches. Furthermore, research attempts will be surveyed for JNDs for audio, smell, haptics and gustatory signals, as well as cross-modality/media efforts. Finally, possible future directions and opportunities are analysed and discussed.
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页码:3706 / 3721
页数:16
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