Blind Image Quality Assessment for Stereoscopic Images Using Binocular Guided Quality Lookup and Visual Codebook

Abstract

The field of assessing three-dimensional (3-D) visual experience is challenging. In this paper, we propose a new blind image quality assessment for stereoscopic images by using binocular guided quality lookup and visual codebook. To be more specific, in the training stage, we construct phase-tuned quality lookup (PTQL) and phase-tuned visual codebook (PTVC) from the binocular energy responses based on stimuli from different spatial frequencies, orientations, and phase shifts. In the test stage, blind quality pooling can be easily achieved by searching the PTQL and PTVC, and the quality score is obtained by averaging the largest values of all patch's quality. Experimental results on three 3-D image quality assessment databases demonstrate that in comparison with the most related existing methods, the devised algorithm achieves high consistency alignment with subjective assessment and low-complexity pooling.