Loughborough University
Browse
PID3768645.pdf (486.15 kB)

A full-reference stereoscopic image quality metric based on binocular energy and regression analysis

Download (486.15 kB)
conference contribution
posted on 2015-11-05, 14:36 authored by Chathura Galkandage, J. Calic, Varuna De Silva, Safak DoganSafak Dogan
The recent developments of 3D media technology have brought to life numerous applications of interactive entertainment such as 3D cinema, 3DTV and gaming. However, due to the data intensive nature of 3D visual content, a number of research challenges have emerged. In order to optimise the end-to-end content life-cycle, from capture to processing and delivery, Quality of Experience (QoE) has become a major driving factor. This paper presents a human-centric approach to quality estimation of 3D visual content. A full reference quality assessment method for stereoscopic images is proposed. It is based on a Human Visual System (HVS) model to estimate subjective scores of registered stereoscopic images subjected to compression losses. The model has been trained with four publicly available registered stereoscopic image databases and a fixed relationship between subjective scores and the model has been determined. The high correlation of the relationship over a large number of stimuli has proven its consistency over the state-of-the-art.

History

School

  • Loughborough University London

Published in

3DTV Conference (3DTV-CON 2015)

Citation

GALKANDAGE, C. ...et al., 2015. A full-reference stereoscopic image quality metric based on binocular energy and regression analysis. IN: 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON), Lisbon, 8-10th July.

Publisher

© The Crown. Published by the IEEE

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2015

Notes

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.

ISBN

978146738090415

Language

  • en

Location

Lisbon, Portugal

Usage metrics

    Loughborough Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC