A Novel No-reference Objective Stereoscopic Video Quality Assessment Method Based on Visual Saliency Analysis

This paper proposes a no-reference objective stereoscopic video quality assessment method with the motivation that making the effect of objective experiments close to that of subjective way. We believe that the image regions with different visual salient degree should not have the same weights when designing an assessment metric. Therefore, we firstly use GBVS algorithm to each frame pairs and separate both the left and right viewing images into the regions with strong, general and week saliency. Besides, local feature information like blockiness, zero-crossing and depth are extracted and combined with a mathematical model to calculate a quality assessment score. Regions with different salient degree are assigned with different weights in the mathematical model. Experiment results demonstrate the superiority of our method compared with the existed state-of-the-art no-reference objective Stereoscopic video quality assessment methods.