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Statistical hypothesis testing as a novel perspective of pooling for image quality assessment

Zhu, R. ORCID: 0000-0002-9944-0369, Zhou, F., Yang, W. & Jing-Hao, X. (2023). Statistical hypothesis testing as a novel perspective of pooling for image quality assessment. Signal Processing: Image Communication, 114, article number 116942. doi: 10.1016/j.image.2023.116942


Image quality assessment is usually achieved by pooling local quality scores. However, commonly used pooling strategies, based on simple sample statistics, are not always sensitive to distortions. In this short communication, we propose a novel perspective of pooling: reliable pooling through statistical hypothesis testing, which enables effective detection of subtle changes of population parameters when the underlying distribution of local quality scores is affected by distortions. To illustrate the significance of this novel perspective, we design a new pooling strategy utilising simple one-sided one-sample t-test. The experiments on benchmark databases show the reliability of hypothesis testing-based pooling, compared with state-of-the-art pooling strategies.

Publication Type: Article
Additional Information: This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher Keywords: Image quality assessment, pooling strategy, hypothesis testing
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HF Commerce
Departments: Bayes Business School > Actuarial Science & Insurance
SWORD Depositor:
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Available under License Creative Commons Attribution Non-commercial No Derivatives.


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