Visual perception of computer-generated stereoscopic pictures: Toward the impact of image resolution

Abstract

In comparison with the generation of monoscopic images, the time cost of rendering stereoscopic images is doubled. When generating stereoscopic images by computer algorithms, it is desirable to save the computational expense by decreasing the image resolution, without degrading the visual perceptual quality of the images. In this work, to evaluate the perceptual visual quality of computer-generated stereoscopic images (CGSIs), a data set consisting of stereoscopic images created with different horizontal and vertical resolutions was constructed. First, a series of subjective experiments for the analysis of various perceptual situations was conducted. The experimental results show that when the original image resolution was reduced by half, the image difference was not perceptible. In addition, based on full-reference (FR) and no-reference (NR) image quality measurement (IQM), a combined FR-and-NR CGSIQA model was established to predict perceptual quality. We perform weighting calculations for different combinations of FR and NR. The experimental results show that the proposed model significantly outperforms all the classical models.