A new objective stereoscopic image assessment model based on stereoscopic perception

In order to establish a stereoscopic image quality assessment method which is consistent with human visual perception, we propose an objective stereoscopic image quality assessment method. It takes into account the strong correlation and high degree of structural between pixels of image. This method contains two models. One is the quality synthetic assessment of left-right view images, which is based on human visual characteristics, we use the Singular Value Decomposition (SVD) that can represent the degree of the distortion, and combine the qualities of left and right images by the characteristics of binocular superposition. The other model is stereoscopic perception quality assessment, due to strong stability of image’s singular value characteristics, we calculate the distance of the singular values and structural characteristic similarity of the absolute difference maps, and utilize the statistical value of the global error to evaluate stereoscopic perception. Finally, we combine two models to describe the stereoscopic image quality. Experimental results show that the correlation coefficients of the proposed assessment method and the human subjective perception are above 0.93, and the mean square errors are all less than 6.2, under JPEG, JP2K compression, Gaussian blurring, Gaussian white noise, H.264 coding distortion, and hybrid cross distortion. It indicates that the proposed stereoscopic objective method is consistent with human visual properties and also of availability.