A Survey of Stereoscopic 3D Just Noticeable Difference Models

Just noticeable difference (JND) for stereoscopic 3D content reflects the maximum tolerable distortion; it corresponds to the visibility threshold of the asymmetric distortions in the left and right contents. The 3D-JND models can be used to improve the efficiency of the 3D compression or the 3D qua...

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Main Authors: Yu Fan, Mohamed-Chaker Larabi, Faouzi Alaya Cheikh, Christine Fernandez-Maloigne
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8601186/
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spelling doaj-eb9242f0404b4d2b92a82e49199b7ce32021-03-29T22:55:33ZengIEEEIEEE Access2169-35362019-01-0178621864510.1109/ACCESS.2018.28872768601186A Survey of Stereoscopic 3D Just Noticeable Difference ModelsYu Fan0Mohamed-Chaker Larabi1https://orcid.org/0000-0003-4511-5381Faouzi Alaya Cheikh2Christine Fernandez-Maloigne3XLIM UMR CNRS 7252, University of Poitiers, Poitiers, FranceXLIM UMR CNRS 7252, University of Poitiers, Poitiers, FranceNorwegian Colour and Visual Computing Laboratory, Norwegian University of Science and Technology, Gjøvik, NorwayXLIM UMR CNRS 7252, University of Poitiers, Poitiers, FranceJust noticeable difference (JND) for stereoscopic 3D content reflects the maximum tolerable distortion; it corresponds to the visibility threshold of the asymmetric distortions in the left and right contents. The 3D-JND models can be used to improve the efficiency of the 3D compression or the 3D quality assessment. Compared to 2D-JND models, the 3D-JND models appeared recently and the related literature is rather limited. In this paper, we give a deep and comprehensive study of the pixel-based 3D-JND models. To our best knowledge, this is the first review on 3D-JND models. Each model is briefly described by giving its rationale and main components in addition to providing exhaustive information about the targeted application, the pros, and cons. Moreover, we present the characteristics of the human visual system presented in these models. In addition, we analyze and compare the 3D-JND models thoroughly using qualitative and quantitative performance evaluation based on Middlebury stereo datasets. Besides, we measure the JND thresholds of the asymmetric distortion based on psychophysical experiments and compare these experimental results to the estimates from the 3D-JND models in order to evaluate the accuracy of each model.https://ieeexplore.ieee.org/document/8601186/Human visual systemjust noticeable difference (JND)3D compression3D-JND models3D quality assessment
collection DOAJ
language English
format Article
sources DOAJ
author Yu Fan
Mohamed-Chaker Larabi
Faouzi Alaya Cheikh
Christine Fernandez-Maloigne
spellingShingle Yu Fan
Mohamed-Chaker Larabi
Faouzi Alaya Cheikh
Christine Fernandez-Maloigne
A Survey of Stereoscopic 3D Just Noticeable Difference Models
IEEE Access
Human visual system
just noticeable difference (JND)
3D compression
3D-JND models
3D quality assessment
author_facet Yu Fan
Mohamed-Chaker Larabi
Faouzi Alaya Cheikh
Christine Fernandez-Maloigne
author_sort Yu Fan
title A Survey of Stereoscopic 3D Just Noticeable Difference Models
title_short A Survey of Stereoscopic 3D Just Noticeable Difference Models
title_full A Survey of Stereoscopic 3D Just Noticeable Difference Models
title_fullStr A Survey of Stereoscopic 3D Just Noticeable Difference Models
title_full_unstemmed A Survey of Stereoscopic 3D Just Noticeable Difference Models
title_sort survey of stereoscopic 3d just noticeable difference models
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description Just noticeable difference (JND) for stereoscopic 3D content reflects the maximum tolerable distortion; it corresponds to the visibility threshold of the asymmetric distortions in the left and right contents. The 3D-JND models can be used to improve the efficiency of the 3D compression or the 3D quality assessment. Compared to 2D-JND models, the 3D-JND models appeared recently and the related literature is rather limited. In this paper, we give a deep and comprehensive study of the pixel-based 3D-JND models. To our best knowledge, this is the first review on 3D-JND models. Each model is briefly described by giving its rationale and main components in addition to providing exhaustive information about the targeted application, the pros, and cons. Moreover, we present the characteristics of the human visual system presented in these models. In addition, we analyze and compare the 3D-JND models thoroughly using qualitative and quantitative performance evaluation based on Middlebury stereo datasets. Besides, we measure the JND thresholds of the asymmetric distortion based on psychophysical experiments and compare these experimental results to the estimates from the 3D-JND models in order to evaluate the accuracy of each model.
topic Human visual system
just noticeable difference (JND)
3D compression
3D-JND models
3D quality assessment
url https://ieeexplore.ieee.org/document/8601186/
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