No‐reference stereoscopic image quality assessment based on saliency‐guided binocular feature consolidation
Xiaogang Xu, Yang Zhao, Yong Shan Ding · Electronics Letters · 2017
Different from traditional methods depending on the procedure of intermediate ‘cyclopean’ view construction, a novel framework based on saliency‐guided multi‐scale feature consolidation for stereoscopic image quality assessment is proposed. For quality representation, the underlying features are extracted from three aspects: (i) global natural statistics features, (ii) local spatial and spectral entropy features and (iii) the kurtosis and skew of disparity distribution. Then the binocular features are consolidated by a saliency‐guided weighted process. Finally, a machine learning technique of support vector regression is used for objective quality mapping. Experimental results demonstrate the promising performance of the proposed method.