Stereoscopic video quality assessment model based on spatial-temporal structural information
Most of the existing 3D video quality assessment methods estimate the quality of each view independently and then pool them into unique objective score. Besides, they seldom take the motion information of adjacent frames into consideration. In this paper, we propose an effective stereoscopic video quality assessment method which focuses on the inter-view correlation of spatial-temporal structural information extracted from adjacent frames. The metric jointly represents and evaluates two views. By selecting salient pixels to be processed and discarding the others, the processing speed is significantly improved. Experimental results on our stereoscopic video database show that the proposed algorithm correlates well with subjective scores.