HVS-based quality assessment metrics for 3-D images

Li, Sumei and Xiang, Wei and Cheng, Fuwei and Zhao, Ruichao and Hou, Chunping (2010) HVS-based quality assessment metrics for 3-D images. In: 2nd WRI Global Congress on Intelligent Systems (GCIS 2010) , 16-17 Dec 2010, Wuhan, China.

Abstract

Significant efforts from both the academia and industry have been devoted to advance three-dimensional (3-D) imaging technologies. However, accurate and easy-to-use visual quality assessment metrics still lack for 3-D images. In this paper, we propose three objective quality assessment metrics for 3-D images taking into consideration a set of relevant visual characteristic factors, including contrast sensitivity, multichannel and binocular parallax characteristics. The human visual signal-to-noise ratio (HVSNR), parallax distortion ratio (PDR), and different peak signal-to-noise ratio (DPSNR) are the three independent objective quality assessment metrics proposed in this paper. Experimental results show that the quality assessment results based upon the proposed metrics are consistent with the quality grades obtained by subjective assessment.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Copyright and Reprint Permissions: Abstracting is permitted with credit to the source.
Depositing User: epEditor USQ
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering
Date Deposited: 12 Mar 2012 12:09
Last Modified: 03 Jul 2013 01:02
Uncontrolled Keywords: 3-D image; quality assessment; binocular parallax; contrast sensitivity; human visual signal-to-noise ratio (HVSNR)
Fields of Research (FOR2008): 09 Engineering > 0906 Electrical and Electronic Engineering > 090606 Photonics and Electro-Optical Engineering (excl. Communications)
09 Engineering > 0906 Electrical and Electronic Engineering > 090609 Signal Processing
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: doi: 10.1109/GCIS.2010.273
URI: http://eprints.usq.edu.au/id/eprint/20688

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