Physics Maths Engineering
Institution: rnfinity
Email: info@rnfinity.com
Rui Zhu,
Rui Zhu
Institution: a Faculty of Actuarial Science and Insurance, Bayes Business School, City
Email: info@rnfinity.com
Fei Zhou,
Wenming Yang
Wenming Yang
Institution: Department of Electronic Engineering, Graduate School at Shenzhen
Email: info@rnfinity.com
Peer Reviewed
© attribution CC-BY
29 Views
Doi: https://doi.org/10.1016/j.image.2023.116942
2023-05-10Image 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.