@article {12741,
	title = {Estimating Visual Saliency Through Single Image Optimization},
	journal = {IEEE Signal Processing Letters},
	volume = {20},
	year = {2013},
	month = {2013/9},
	pages = {845-848},
	chapter = {845},
	abstract = {This letter presents a novel approach for visual saliency estimation through single image optimization. Instead of directly mapping visual features to saliency values with a unified model, we treat regional saliency values as the optimization objective on each single image. By using a quadratic programming framework, our approach can adaptively optimize the regional saliency values on each specific image to simultaneously meet multiple saliency hypotheses on visual rarity, center-bias and mutual correlation. Experimental results show that our approach can outperform 14 state-of-the-art approaches on a public image benchmark.},
	keywords = {Quadratic programming; single image optimization; visual saliency},
	isbn = {1070-9908},
	doi = {10.1109/LSP.2013.2268868},
	author = {LiJia(博士后)；*TianYonghong；DuanLingyu；HuangTiejun}
}
