Full-reference quality assessment for stereoscopic images based on binocular vision model
Chaoyi Lin, Zhibo Chen, Ning Fang Liao · 2016
As the demand and supply for 3D technologies grows, the quality assessment of stereoscopic content is both demanding and increasingly urgent. This paper proposes a novel 3D images quality assessment (IQA) algorithm which is based on the Binocular Rivalry model and the Summation and Difference model. Both the influence of distorted disparity information on perceptual quality and the binocular rivalry mechanism of HVS are considered in our algorithm. Since disparity map is not utilized in our algorithm, it saves the complex computation of disparity map and improves the robustness of our algorithm. Experiment results shows that our algorithm outperforms well-known 3D IQA metrics on LIVE database and delivers competitive performance on Waterloo database. The cross database validation indicates that our algorithm is stable on different database.