A virtual view PSNR estimation method for 3-D Videos

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

32 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Article number7321813
Pages (from-to)134-140
Journal / PublicationIEEE Transactions on Broadcasting
Volume62
Issue number1
Online published6 Nov 2015
Publication statusPublished - Mar 2016

Abstract

In three-dimensional videos (3-DVs) with n-view texture videos plus n-view depth maps, virtual views can be synthesized from neighboring texture videos and the associated depth maps. To evaluate the system performance or guide the rate-distortion-optimization process of 3-DV coding, the distortion/PSNR of the virtual view should be calculated by measuring the quality difference between the virtual view synthesized by compressed 3-DVs with one synthesized by uncompressed 3-DVs, which increases the complexity of a 3-DV system. In order to reduce the complexity of 3-DV system, it is better to estimate virtual view distortions/PSNR directly without rendering virtual views. In this paper, the virtual view synthesis procedure and the distortion propagation from existing views to virtual views are analyzed in detail, and then a virtual view distortion/PSNR estimation method is derived. Experimental results demonstrate that the proposed method could estimate PSNRs of virtual views accurately. The squared correlation coefficient and root of mean squared error between the estimated PSNRs by the proposed method and the actual PSNRs are 0.998 and 2.012 on average for all the tested sequences. Since the proposed method is implemented row-by-row independently, it is also friendly for parallel design. The execute time for each row of pictures with 1024×768 resolution is only 0.079 s, while for pictures with 1920×1088 resolution it is only 0.155 s.

Research Area(s)

  • 3DV, Distortion estimation, video coding

Citation Format(s)

A virtual view PSNR estimation method for 3-D Videos. / Yuan, Hui; Kwong, Sam; Wang, Xu et al.
In: IEEE Transactions on Broadcasting, Vol. 62, No. 1, 7321813, 03.2016, p. 134-140.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review