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Subjective assessment of image quality induced saliency variation

Leveque, Lucie, Zhang, Wei and Liu, Hantao ORCID: https://orcid.org/0000-0003-4544-3481 2019. Subjective assessment of image quality induced saliency variation. Presented at: The 26th IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, 22-25 September 2019. 2019 IEEE International Conference on Image Processing (ICIP). IEEE, pp. 1024-1028. 10.1109/ICIP.2019.8803736

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Abstract

Our previous study has shown that image distortions cause saliency distraction, and that visual saliency of a distorted image differs from that of its distortion-free reference. Being able to measure such distortion-induced saliency variation (DSV) significantly benefits algorithms for automated image quality assessment. Methods of quantifying DSV, however, remain unexplored due to the lack of a benchmark. In this paper, we build a benchmark for the measurement of DSV through a subjective study. Sixteen experts in computer vision were asked to compare saliency maps of distorted images to the corresponding saliency maps of the original images. All saliency maps were rendered from ground truth human fixations. A statistical analysis is performed to reveal the behaviours and properties of human assessment of the saliency variation. The benchmark is made publicly available to the research community.

Item Type: Conference or Workshop Item - published (Paper)
Date Type: Published Online
Status: Published
Schools: Schools > Computer Science & Informatics
Publisher: IEEE
ISBN: 978-1-5386-6250-2
ISSN: 1522-4880
Date of First Compliant Deposit: 15 May 2019
Last Modified: 14 May 2026 09:45
URI: https://orca.cardiff.ac.uk/id/eprint/122080

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