Abstract
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 collected in a controlled lab environment. 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.
Original language | English |
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Title of host publication | 2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings |
Publisher | IEEE |
Pages | 116-120 |
Number of pages | 5 |
Volume | 2020 |
ISBN (Electronic) | 9781728163956 |
DOIs | |
Publication status | Published - 31 Dec 2020 |
Event | 2020 IEEE International Conference on Image Processing, ICIP 2020 - Virtual, Abu Dhabi, UAE United Arab Emirates Duration: 25 Sept 2020 → 28 Sept 2020 |
Publication series
Name | Proceedings - International Conference on Image Processing, ICIP |
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Volume | 2020-October |
ISSN (Print) | 1522-4880 |
Conference
Conference | 2020 IEEE International Conference on Image Processing, ICIP 2020 |
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Country/Territory | UAE United Arab Emirates |
City | Virtual, Abu Dhabi |
Period | 25/09/20 → 28/09/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
Keywords
- Image quality assessment
- mean opinion score
- objective metric
- subjective testing
- visual perception
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Signal Processing