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Communication Dans Un Congrès Année : 2016

On the performance of 3D just noticeable difference models

Résumé

The just noticeable difference (JND) notion reflects the maximum tolerable distortion. It has been extensively used for the optimization of 2D applications. For stereoscopic 3D (S3D) content, this notion is different since it relies on different mechanisms linked to our binocular vision. Unlike 2D, 3D-JND models appeared recently and the related literature is rather limited. These models can be used for the sake of compression and quality assessment improvement for S3D content. In this paper, we propose a deep and comparative study of the existing 3D-JND models. Additionally, in order to analyze their performance, the 3D-JND models have been integrated in recent metric dedicated to stereoscopic image quality assessment (SIQA). The results are reported on two widely used S3D image databases.
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Dates et versions

hal-01405748 , version 1 (30-11-2016)

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Citer

Yu Fan, Mohamed-Chaker Larabi, Cheikh Faouzi Alaya, Christine Fernandez-Maloigne. On the performance of 3D just noticeable difference models. IEEE International Conference on Image Processing (ICIP), Sep 2016, Phoenix, AZ, United States. pp.1017-1021, ⟨10.1109/ICIP.2016.7532511⟩. ⟨hal-01405748⟩
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