A benchmark of variance of opinion scores in image quality assessment

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:	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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