Perceptual stereoscopic images quality assessment method based on visual adaptable characteristics

Zhi Zheng; Yun Liu; Yun Liu

doi:10.1117/1.OE.58.7.073101

3 July 2019 Perceptual stereoscopic images quality assessment method based on visual adaptable characteristics

Zhi Zheng, Yun Liu, Yun Liu

Author Affiliations +

Funded by: Fundamental Research Funds for the Central Universities

Optical Engineering, Vol. 58, Issue 7, 073101 (July 2019). https://doi.org/10.1117/1.OE.58.7.073101

Abstract

The quality assessment of stereoscopic images plays an important role in various three-dimensional (3-D) areas and encounters more problems than two-dimensional (2-D) image quality assessment. We propose a perceptual full-reference quality assessment model by considering human adaptable double visual channel. Human binocular combination characteristics and depth perception are both considered in this model, and an adaptable gain-control model is adopted to assign appropriate weights to the information of human visual channels. Experimental results indicate that the proposed algorithm can serve as an efficient predictive image quality feature, which delivers not only highly competitive prediction accuracy but also moderate computational complexity.

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Zhi Zheng, Yun Liu, and Yun Liu "Perceptual stereoscopic images quality assessment method based on visual adaptable characteristics," Optical Engineering 58(7), 073101 (3 July 2019). https://doi.org/10.1117/1.OE.58.7.073101

Received: 7 April 2019; Accepted: 7 June 2019; Published: 3 July 2019

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KEYWORDS

Visual process modeling

Image quality

Performance modeling

3D modeling

Visualization

Data modeling

3D image processing

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