An objective quality assessment metric for stereoscopic images based on just noticeable distortion
Mei Yu · Journal of Optoelectronics·laser · 2012
In this paper,combining with the just noticeable distortion(JND) model and features of singular values,an objective quality assessment metric for stereoscopic images based on just noticeable distortion is proposed.The proposed metric consists of image quality assessment and depth perception assessment.Firstly,stereoscopic features are obtained by extracting the features of image quality and depth perception.Then,the features are fused according to different types of distortions.Finally,the values of objective assessment are predicted by support vector regression(SVR).Experimental results show that by applying the proposed model to stereoscopic test database,for either distortion quality assessment or mixture distortion quality assessment,the pearson linear correlation coefficient(CC) index reaches 0.94,and the spearman rank order correlation coefficient(SROCC) index reaches 0.92,which indicates that the model is fairly good and can predict human visual perception well.