Image Quality Assessment for DIBR Synthesized Views using Elastic Metric

Frames of free viewpoint video (FVV) synthesized with depth image-based rendering (DIBR) mainly contains special local artifacts like geometric distortions, in which the shape of objects may be stretched/bent. Human observers tend to perceive such local severe deformations instead of consistent shifting artifacts that penalized by most of the existing metrics. Elastic metric is capable of measuring the difference in stretching or bending between two curves, and thus is suitable for evaluating such geometric distortions. In this paper, an elastic metric based image quality assessment (EM-IQA) scheme is proposed by first selecting local distortion regions and then quantifying the deformations of curves. According to the experimental results on the IRCCyn/IVC DIBR image database, the proposed EM-IQA outperforms the state of the art metrics designed for synthesized images and obtains a gain of 6.97% in pearson correlation compared to the second best performing MP-PSNRreduced.