About this Journal Submit a Manuscript Table of Contents
Journal of Electrical and Computer Engineering
Volume 2012 (2012), Article ID 436031, 12 pages
http://dx.doi.org/10.1155/2012/436031
Research Article

No-Reference Stereoscopic IQA Approach: From Nonlinear Effect to Parallax Compensation

Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Minhang District, Shanghai 200240, China

Received 20 April 2012; Revised 31 August 2012; Accepted 22 September 2012

Academic Editor: Paul Dan Cristea

Copyright © 2012 Ke Gu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The last decade has seen a booming of the applications of stereoscopic images/videos and the corresponding technologies, such as 3D modeling, reconstruction, and disparity estimation. However, only a very limited number of stereoscopic image quality assessment metrics was proposed through the years. In this paper, we propose a new no-reference stereoscopic image quality assessment algorithm based on the nonlinear additive model, ocular dominance model, and saliency based parallax compensation. Our studies using the Toyama database result in three valuable findings. First, quality of the stereoscopic image has a nonlinear relationship with a direct summation of two monoscopic image qualities. Second, it is a rational assumption that the right-eye response has the higher impact on the stereoscopic image quality, which is based on a sampling survey in the ocular dominance research. Third, the saliency based parallax compensation, resulted from different stereoscopic image contents, is considerably valid to improve the prediction performance of image quality metrics. Experimental results confirm that our proposed stereoscopic image quality assessment paradigm has superior prediction accuracy as compared to state-of-the-art competitors.