Hybrid Integration of Visual Attention Model into Image Quality Metric
Integrating the visual attention (VA) model into an objective image quality metric is a rapidly evolving area in modern image quality assessment (IQA) research due to the significant opportunities the VA information presents. So far, in the literature, it has been suggested to use either a task-free...
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Veröffentlicht in: | IEICE transactions on information and systems 2015-01, Vol.97 (11), p.2971-2973 |
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description | Integrating the visual attention (VA) model into an objective image quality metric is a rapidly evolving area in modern image quality assessment (IQA) research due to the significant opportunities the VA information presents. So far, in the literature, it has been suggested to use either a task-free saliency map or a quality-task one for the integration into quality metric. A hybrid integration approach which takes the advantages of both saliency maps is presented in this paper. We compare our hybrid integration scheme with existing integration schemes using simple quality metrics. Results show that the proposed method performs better than the previous techniques in terms of prediction accuracy. |
doi_str_mv | 10.1587/transinf.2014EDL8141 |
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source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; J-STAGE (Japan Science & Technology Information Aggregator, Electronic) Freely Available Titles - Japanese |
subjects | Accuracy Assessments Evolution Image quality Visual |
title | Hybrid Integration of Visual Attention Model into Image Quality Metric |
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