DoganS-IEEEjournal_Nov2016.pdf (9.18 MB)
Stereoscopic video quality assessment using binocular energy
journal contribution
posted on 2016-12-06, 11:39 authored by Chathura Galkandage, J. Calic, Safak DoganSafak Dogan, Jean-Yves GuillemautStereoscopic 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.
Funding
This work used stereoscopic video sequences from the ROMEO project (grant number: 287896) of the EC FP7 ICT collaborative research programme.
History
School
- Loughborough University London
Published in
IEEE Journal of Selected Topics in Signal ProcessingVolume
11Issue
1Pages
102 - 112Citation
GALKANDAGE, C. ...et al., 2017. Stereoscopic video quality assessment using binocular energy. IEEE Journal of Selected Topics in Signal Processing, 11(1), pp.102-112.Publisher
© IEEEVersion
- AM (Accepted Manuscript)
Acceptance date
2016-11-11Publication date
2016-11-22Notes
© 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.ISSN
1932-4553eISSN
1941-0484Publisher version
Language
- en
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