research-article

Underwater Image Quality Assessment from Synthetic to Real-world: Dataset and Objective Method

Authors:

Hongwei YingAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications and Applications, Volume 20, Issue 3

Article No.: 71, Pages 1 - 23

https://doi.org/10.1145/3624983

Published: 23 October 2023 Publication History

Abstract

The complicated underwater environment and lighting conditions lead to severe influence on the quality of underwater imaging, which tends to impair underwater exploration and research. To effectively evaluate the quality of underwater images, an underwater image quality assessment dataset is constructed from synthetic to real-world, and then a new objective underwater image assessment method based on the characteristics of the underwater imaging is proposed (UICQA). Specifically, to address the lack of a publicly available datasets and more accurately quantify the quality of underwater images, a subjective underwater image quality assessment dataset from synthetic to real-world underwater images, named USRD, is constructed. Considering that the transmission map can effectively reflect the characteristics of the underwater imaging, statistical features are effectively extracted from the transmission map for distinguishing underwater images of different quality. Further, considering that the transmission map negatively correlates with scene depth, a local-to-global transmission map weighted contrast feature is constructed. Additionally, the color features of human perception and texture features based on fractal dimensions are proposed. Finally, the experimental results show that the proposed UICQA method exhibits the highest correlation with ground truth scores compared to state-of-the-art UIQA methods.

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Cited By

Jiang QYi XOuyang LZhou JWang Z(2025)Toward Dimension-Enriched Underwater Image Quality AssessmentIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.346692535:2(1385-1398)Online publication date: Feb-2025
https://doi.org/10.1109/TCSVT.2024.3466925
Wu SJiang QYue GWang SZhai G(2025)Generalizable Underwater Image Quality Assessment With Curriculum Learning-Inspired Domain AdaptionIEEE Transactions on Broadcasting10.1109/TBC.2024.351196271:1(252-263)Online publication date: Mar-2025
https://doi.org/10.1109/TBC.2024.3511962
Duminil AIeng SGruyer D(2024)Assessing fidelity in synthetic datasets: A multi-criteria combination methodology2024 27th International Conference on Information Fusion (FUSION)10.23919/FUSION59988.2024.10706451(1-8)Online publication date: 8-Jul-2024
https://doi.org/10.23919/FUSION59988.2024.10706451
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Index Terms

Underwater Image Quality Assessment from Synthetic to Real-world: Dataset and Objective Method
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods

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cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 20, Issue 3

March 2024

665 pages

EISSN:1551-6865

DOI:10.1145/3613614

Editor:
Abdulmotaleb El Saddik
Mohamed Bin Zayed University of Artificial Intelligence, UAE and University of Ottawa, Canada

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Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Publication History

Published: 23 October 2023

Online AM: 20 September 2023

Accepted: 12 September 2023

Revised: 10 August 2023

Received: 15 September 2022

Published in TOMM Volume 20, Issue 3

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Natural Science Foundation of China
Zhejiang Natural Science Foundation of China
Scientific Research Fund of Zhejiang Provincial Education Department
Natural Science Foundation of Ningbo, China

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Cited By

Jiang QYi XOuyang LZhou JWang Z(2025)Toward Dimension-Enriched Underwater Image Quality AssessmentIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.346692535:2(1385-1398)Online publication date: Feb-2025
https://doi.org/10.1109/TCSVT.2024.3466925
Wu SJiang QYue GWang SZhai G(2025)Generalizable Underwater Image Quality Assessment With Curriculum Learning-Inspired Domain AdaptionIEEE Transactions on Broadcasting10.1109/TBC.2024.351196271:1(252-263)Online publication date: Mar-2025
https://doi.org/10.1109/TBC.2024.3511962
Duminil AIeng SGruyer D(2024)Assessing fidelity in synthetic datasets: A multi-criteria combination methodology2024 27th International Conference on Information Fusion (FUSION)10.23919/FUSION59988.2024.10706451(1-8)Online publication date: 8-Jul-2024
https://doi.org/10.23919/FUSION59988.2024.10706451
Wen HSong XChen XWei YNie LChua THui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Simple but Effective Raw-Data Level Multimodal Fusion for Composed Image RetrievalProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657727(229-239)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657727
Li XXu HJiang GYu MChen YLuo TYing H(2024)Underwater Image Quality Assessment Based on Multiscale and Antagonistic EnergyIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2023.333865773(1-14)Online publication date: 2024
https://doi.org/10.1109/TIM.2023.3338657

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