Stereo image quality assessment considering the difference of statistical feature in early visual pathway

Human visual theory is closely related to stereo image quality assessment (SIQA), which determines whether the evaluation results of SIQA method can keep good consistency with subjective perception. Many SIQA methods are not fully based on human visual theory, so there is still room for improvement. The research on the visual system tends to the dorsal and ventral pathways, which ignores the information differences in the early visual pathways. It is worth noting that the ON and OFF receptive fields in retinal ganglion cells (RGCs) respond asymmetrically to the statistical features of images. Inspired by this, in this paper, we propose an SIQA method based on monocular and binocular visual features, which takes into account the difference of ON and OFF response features in early visual pathways. Moreover, the different information interaction mechanisms of visual cortex are used to fuse the response maps information of left and right images. Final, monocular and binocular features are extracted and sent to support vector regression (SVR) for quality prediction. Experimental results show that the proposed method is superior to several mainstream SIQA metrics on four publicly available stereo image databases.