Crowdsourced Quality Assessment of Enhanced Underwater Images: a Pilot Study

Hanhe Lin, Hui Men, Yijun Yan, Jinchang Ren, Dietmar Saupe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Underwater image enhancement (UIE) is essential for a high-quality underwater optical imaging system. While a number of UIE algorithms have been proposed in recent years, there is little study on image quality assessment (IQA) of enhanced underwater images. In this paper, we conduct the first crowdsourced subjective IQA study on enhanced underwater images. We chose ten state-of-the-art UIE algorithms and applied them to yield enhanced images from an underwater image benchmark. Their latent quality scales were reconstructed from pair comparison. We demonstrate that the existing IQA metrics are not suitable for assessing the perceived quality of enhanced underwater images. In addition, the overall performance of 10 UIE algorithms on the benchmark is ranked by the newly proposed simulated pair comparison of the methods.
Original languageEnglish
Title of host publication2022 14th International Conference on Quality of Multimedia Experience (QoMEX)
PublisherIEEE Computer Society
Number of pages4
ISBN (Print)9781665487948, 9781665487955
DOIs
Publication statusPublished - 18 Oct 2022
Event14th International Conference on Quality of Multimedia Experience (QoMEX): Towards Technology for Well-Being and Excellence - Lippstadt, Germany
Duration: 5 Sep 20227 Sep 2022
https://ieeexplore.ieee.org/xpl/conhome/9900491/proceeding

Conference

Conference14th International Conference on Quality of Multimedia Experience (QoMEX)
Country/TerritoryGermany
CityLippstadt
Period5/09/227/09/22
Internet address

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