Quality assessment of synthetic viewpoint stereo image with multi-feature fusion

Abstract

A multi-feature fusion method was proposed,the features of the distortion areas,the distortion edges and the singular value were fused.Firstly,the distortion areas corresponding to the human eyes were obtained by using the parallax and the threshold,and then the average structural similarity in these areas was calculated.Secondly,the distorted edges in the synthetic viewpoint edge image were extracted,and then the average structural similarity was calculated.Thirdly,the difference between the original image and the distorted image singular value was calculated.Finally,the three features were fused to obtain the final objective quality score.The experiment was carried out on the synthetic viewpoint stereo image library.The experimental results show that the Pearson linear correlation coefficient and the Spearman correlation coefficient are both higher than 0.86.Compared with the existing assessment methods,it can better reflect the quality of synthetic viewpoint stereo images.

Keywords

• virtual viewpoint;stereo image;quality assessment;feature fusion;human visual characteristic