Stereoscopic Image Quality Assessment Based on Depth and Texture Information

Abstract

With the increasing growth of multimedia applications over the networking in recent years, users have put forward much higher requirements for multimedia signals, particularly for image/video signal's quality of experience (QoE) than before. The objective approach of image quality assessment (IQA) plays an important role for the development of compression standards and various multimedia applications. However, the quality assessment of stereoscopic (3-D) 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) 3-D IQA method to measure the quality of the distorted images. The properties of the depth component, structure component, and gradient component are taken into account to establish the proposed metric. The experimental results show that the proposed metric is highly consistent with the subjective test scores compared with the existing related metrics. In addition, the main significance of the proposed metric is that it not only could effectively evaluate the quality of 3-D image but also has a satisfied effect for measuring the quality of 2-D image.