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Stereoscopic Video Quality Assessment Using Binocular Energy

Galkandage, Chathura, Calic, Janko, Dogan, S and Guillemaut, Jean-Yves (2017) Stereoscopic Video Quality Assessment Using Binocular Energy Journal of Selected Topics in Signal Processing, 11 (1). pp. 102-112.

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Stereoscopic imaging is becoming increasingly popular. However, to ensure the best quality of experience, there is a need to develop more robust and accurate objective metrics for stereoscopic content quality assessment. Existing stereoscopic image and video metrics are either extensions of conventional 2D metrics (with added depth or disparity information) or are based on relatively simple perceptual models. Consequently, they tend to lack the accuracy and robustness required for stereoscopic content quality assessment. This paper introduces full-reference stereoscopic image and video quality metrics based on a Human Visual System (HVS) model incorporating important physiological findings on binocular vision. The proposed approach is based on the following three contributions. First, it introduces a novel HVS model extending previous models to include the phenomena of binocular suppression and recurrent excitation. Second, an image quality metric based on the novel HVS model is proposed. Finally, an optimised temporal pooling strategy is introduced to extend the metric to the video domain. Both image and video quality metrics are obtained via a training procedure to establish a relationship between subjective scores and objective measures of the HVS model. The metrics are evaluated using publicly available stereoscopic image/video databases as well as a new stereoscopic video database. An extensive experimental evaluation demonstrates the robustness of the proposed quality metrics. This indicates a considerable improvement with respect to the state-of-the-art with average correlations with subjective scores of 0.86 for the proposed stereoscopic image metric and 0.89 and 0.91 for the proposed stereoscopic video metrics.

Item Type: Article
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Dogan, S
Date : February 2017
DOI : 10.1109/JSTSP.2016.2632045
Copyright Disclaimer : © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords : Stereoscopic video, HVS model, Quality metric.
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 25 Nov 2016 18:10
Last Modified : 16 Jan 2019 17:10

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