Lou, Jianxun, Wu, Xinbo, Wu, Yingying, Corcoran, Padraig  ORCID: https://orcid.org/0000-0001-9731-3385, Colombo, Gualtiero, Whitaker, Roger ORCID: https://orcid.org/0000-0002-8473-1913 and Liu, Hantao ORCID: https://orcid.org/0000-0003-4544-3481
2024.
A benchmark of variance of opinion scores in image quality assessment.
Presented at: IEEE International Conference on Image Processing,
Abu Dhabi,
27-30 October 2024.
Proceedings of International Conference on Image Processing.
IEEE,
pp. 1232-1238.
10.1109/ICIP51287.2024.10647649
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Abstract
Mean opinion score (MOS) has been used as the benchmark to measure the perceived quality of digital images. However, the usefulness of MOS diminishes when a substantial variation between individual opinions occurs. It is critical to measure the stimulus-driven variance of opinion scores (VOS) and scrutinise images that evoke a large VOS, and consequently, use VOS to inform our interpretation of MOS. In this paper, we create a VOS benchmark for individual differences in image quality assessment and analyse the importance of VOS classification as a function of distortion intensity, distortion type and scene content. In addition, a simple yet effective deep learning-based model is built, aiming to identify images with a large variation in viewers’ quality judgements.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Date Type: | Published Online |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Publisher: | IEEE |
| ISBN: | 9798350349405 |
| ISSN: | 1522-4880 |
| Date of First Compliant Deposit: | 21 June 2024 |
| Date of Acceptance: | 6 June 2024 |
| Last Modified: | 07 Nov 2024 12:00 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/170051 |
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