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Title: Estimating just-noticeable distortion for video
Authors: Jia, Y.
Lin, W.
Kassim, A.A. 
Keywords: Contrast sensitivity function (CSF)
Discrete cosine transform (DCT)
Eye movement
Just-noticeable distortion (JND)
Issue Date: Jul-2006
Citation: Jia, Y., Lin, W., Kassim, A.A. (2006-07). Estimating just-noticeable distortion for video. IEEE Transactions on Circuits and Systems for Video Technology 16 (7) : 820-829. ScholarBank@NUS Repository.
Abstract: Just-noticeable distortion (JND), which refers to the maximum distortion that the human visual system (HVS) cannot perceive, plays an important role in perceptual image and video processing. In comparison with JND estimation for images, estimation of the JND profile for video needs to take into account the temporal HVS properties in addition to the spatial properties. In this paper, we develop a spatio-temporal model estimating JND in the discrete cosine tranform domain. The proposed model incorporates the spatio-temporal contrast sensitivity function, the influence of eye movements, luminance adaptation, and contrast masking to be more consistent with human perception. It is capable of yielding JNDs for both still images and video with significant motion. The experiments conducted in this study have demonstrated that the JND values estimated for video sequences with moving objects by the model are in line with the HVS perception. The accurate JND estimation of the video towards the actual visibility bounds can be translated into resource savings (e.g., for band-width/storage or computation) and performance improvement in video coding and other visual processing tasks (such as perceptual quality evaluation, visual signal restoration/enhancement, water-marking, authentication, and error protection). © 2006 IEEE.
Source Title: IEEE Transactions on Circuits and Systems for Video Technology
ISSN: 10518215
DOI: 10.1109/TCSVT.2006.877397
Appears in Collections:Staff Publications

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