Towards an efficient model of visual saliency for objective image quality assessment

Liu, Hantao ORCID: https://orcid.org/0000-0003-4544-3481 and Heynderickx, Ingrid 2012. Towards an efficient model of visual saliency for objective image quality assessment. Presented at: 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, 25-30 March 2012. 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, p. 1153. 10.1109/ICASSP.2012.6288091

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Abstract

Based on “ground truth” eye-tracking data, earlier research [1] shows that adding natural scene saliency (NSS) can improve an objective metric's performance in predicting perceived image quality. To include NSS in a real-world implementation of an objective metric, a computational model instead of eye-tracking data is needed. Existing models of visual saliency are generally designed for a specific domain, and so, not applicable to image quality prediction. In this paper, we propose an efficient model for NSS, inspired by findings from our eye-tracking studies. Experimental results show that the proposed model sufficiently captures the saliency of the eye-tracking data, and applying the model to objective image quality metrics enhances their performance in the same manner as when including eye-tracking data

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	IEEE
ISBN:	978-1-4673-0045-2
Last Modified:	25 Oct 2022 13:07
URI:	https://orca.cardiff.ac.uk/id/eprint/118918

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