HVS-Based Quality Assessment Metrics for 3-D Images

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...

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Bibliographic Details
Main Authors: Sumei Li, Wei Xiang, Fuwei Cheng, Ruichao Zhao, Chunping Hou
Format: Conference Proceeding
Language:English
Subjects:
3-D image
binocular parallax
contrast sensitivity
human visual signal-to-noise ratio (HVSNR)
Humans
Image coding
Image quality
Quality assessment
Sensitivity
Visualization
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Summary: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, multi-channel 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.
ISSN:2155-6083
2155-6091
DOI:10.1109/GCIS.2010.273