Although several 2D quality metrics have been proposed for images and videos, in the case of 3D efforts are only at the initial stages. In this paper, we propose a new full-reference quality metric for 3D content. Our method is modeled around the HVS, fusing the information of both left and right channels, considering color components, the cyclopean views of the two videos and disparity. Performance evaluations showed that our 3D quality metric successfully monitors the degradation of quality caused by several representative types of distortion and it has 86% correlation with the results of subjective evaluations.
@article{arxiv.1803.04624,
title = {A Human Visual System-Based 3D Video Quality Metric},
author = {Amin Banitalebi-Dehkordi and Mahsa T. Pourazad and Panos Nasiopoulos},
journal= {arXiv preprint arXiv:1803.04624},
year = {2018}
}