@inproceedings{3c2e4bcdceb64fc5bcecc7f919f83c38,
title = "Visual attention based image quality assessment",
abstract = "Inspired by the success of structural similarity index (SSIM), some image quality assessment (IQA) methods have been developed recently. To achieve better performance, this paper proposes a new visual attention (VA) model that combines saliency based VA and visual importance based VA, under the assumptions that humans often pay more attention to the regions with important content in the beginning of evaluating a given image and then the regions with poor quality. Then the proposed VA model is incorporated into SSIM. The experiments on LIVE database and TID2008 database demonstrate its improvements over the latest state-of-the-art IQA methods and the information content weighted SSIM measure (IW-SSIM).",
keywords = "human visual system, image quality assessment, saliency, visual attention, visual importance",
author = "Anan Guo and Debin Zhao and Shaohui Liu and Xiaopeng Fan and Wen Gao",
year = "2011",
doi = "10.1109/ICIP.2011.6116375",
language = "英语",
isbn = "9781457713033",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "3297--3300",
booktitle = "ICIP 2011",
note = "2011 18th IEEE International Conference on Image Processing, ICIP 2011 ; Conference date: 11-09-2011 Through 14-09-2011",
}