3D Image Quality Assessment Based on Texture Information
Kai Kang, Xingang Liu, Kaixuan Lu · 2014
With the increasing growth of multimedia applications over the networking in recent years, users have put forward much higher requirements for multimedia quality of experience (QoE) than before. The objective approaches of image quality assessment play an important role for the development of compression standards and various multimedia applications. Nowadays the quality assessment of 3D (stereoscopic) images faces more new challenges, such as depth perception, virtual view synthesis and asymmetric stereo compression. In this paper, we propose a new Full-Reference (FR) 3D image quality assessment method to measure the distortions between the original and distorted images. The metric has taken into account some properties such as depth component, structure component and gradient component. The performance of the proposed metric is compared with other objective image quality assessment metrics. The experimental results have demonstrated that the proposed metric is highly consistent with the subjective test scores. In addition, the main significance of the metric is that it not only can effectively evaluate the quality of 3D image, but also has a good effect in measuring the quality of 2D image.