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CUID: a new study of perceived image quality and its subjective assessment

Lévêque, Lucie, Yang, Ji, Yang, Xiaohan, Guo, Pengfei, Dasalla, Kenneth, Li, Leida, Wu, Yingying and Liu, Hantao ORCID: 2020. CUID: a new study of perceived image quality and its subjective assessment. Presented at: 27th IEEE International Conference on Image Processing (ICIP 2020), United Arab Emirates, 25-28 October 2020.

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Research on image quality assessment (IQA) remains limited mainly due to our incomplete knowledge about human visual perception. Existing IQA algorithms have been designed or trained with insufficient subjective data with a small degree of stimulus variability. This has led to challenges for those algorithms to handle complexity and diversity of real-world digital content. Perceptual evidence from human subjects serves as a grounding for the development of advanced IQA algorithms. It is thus critical to acquire reliable subjective data with controlled perception experiments that faithfully reflect human behavioural responses to distortions in visual signals. In this paper, we present a new study of image quality perception where subjective ratings were reliably collected in a controlled laboratory environment and for a large degree of stimulus content variability. We investigate how quality perception is affected by a combination of different categories of images and different types and levels of distortions. The database will be made publicly available to facilitate calibration and validation of IQA algorithms.

Item Type: Conference or Workshop Item (Paper)
Status: In Press
Schools: Computer Science & Informatics
Date of First Compliant Deposit: 3 June 2020
Date of Acceptance: 16 May 2020
Last Modified: 07 Nov 2022 10:24

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