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

Liu, Hantao 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: 01 Feb 2019 15:00
URI: http://orca.cf.ac.uk/id/eprint/118918

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