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

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5 Citations (Scopus)

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. © 2012 IEEE.
Original languageEnglish
Title of host publication2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP, 25-30 March 2012, Kyoto
Place of PublicationPiscataway
Pages1153-1156
Number of pages4
ISBN (Electronic)978-1-4673-0046-9
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2012) - Kyoto, Japan
Duration: 25 Mar 201230 Mar 2012

Conference

Conference2012 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2012)
Abbreviated titleICASSP 2012
CountryJapan
CityKyoto
Period25/03/1230/03/12
Other2012 IEEE international conference on acoustics, speech, and signal processing

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