Perceptual quality assessment of stereoscopic images based on local and global visual characteristics

Abstract

The quality assessment of stereoscopic images has attracted considerable attention and become an important issue in 3D multimedia applications. The 3D image quality assessment (IQA) encounters many challenges and simple extension of the 2D quality metrics to the 3D case is not satisfying. In this paper, we propose a new perceptual quality assessment scheme for stereoscopic 3D images by considering the local and global visual characteristics. The design of this scheme is motivated by studies on the perception of distorted stereoscopic images. To be more specific, after the log-Gabor filter processing, the local amplitude and phase from the left and right views of the reference and distorted 3D images are utilized as features in local quality evaluation. Meanwhile, the global structure changes of the left and right views are also incorporated into the final quality pooling. The overall 3D quality score is obtained by combining the local and global quality indexes together. The effectiveness of the designed metric is verified on publicly available 3D image quality assessment databases. Experimental results show that the proposed scheme exhibits better performance than other related algorithms in terms of consistency with subjective assessment of stereoscopic 3D images.