Abstract
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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