Studying the added value of visual attention in objective image quality metrics based on eye movement data

Liu, Hantao ORCID: https://orcid.org/0000-0003-4544-3481 and Heynderickx, Ingrid 2010. Studying the added value of visual attention in objective image quality metrics based on eye movement data. Presented at: 2009 16th IEEE International Conference on Image Processing (ICIP), Cairo, Egypt, 7 - 10 November 2009. 2009 16th IEEE International Conference on Image Processing (ICIP). IEEE, p. 3097. 10.1109/ICIP.2009.5414466

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Abstract

Current research on image quality assessment tends to include visual attention in objective metrics to further enhance their performance. A variety of computational models of visual attention are implemented in different metrics, but their accuracy in representing human visual attention is not fully proved yet. Thus, to provide more accurate evidence on whether and to what extent visual attention can be beneficial for objective quality prediction, the use of ¿ground truth¿ visual attention data is highly desired. In this paper, the data of an eye-tracking experiment are integrated in two objective metrics well-known in literature. Experimental results demonstrate that there is indeed a gain in performance including visual attention in objective metrics. The amount of gain in performance tends to depend on the type of objective metric and image distortion

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	IEEE
ISBN:	978-1-4244-5653-6
Last Modified:	25 Oct 2022 13:07
URI:	https://orca.cardiff.ac.uk/id/eprint/118928

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