title: Airport detection in remote sensing images: a method based on saliency map.
abstract: The detection of airport attracts lots of attention and becomes a hot topic recently because of its applications and importance in military and civil aviation fields. However, the complicated background around airports brings much difficulty into the detection. This paper presents a new method for airport detection in remote sensing images. Distinct from other methods which analyze images pixel by pixel, we introduce visual attention mechanism into detection of airport and improve the efficiency of detection greatly. Firstly, Hough transform is used to judge whether an airport exists in an image. Then an improved graph-based visual saliency model is applied to compute the saliency map and extract regions of interest (ROIs). The airport target is finally detected according to the scale-invariant feature transform features which are extracted from each ROI and classified by hierarchical discriminant regression tree. Experimental results show that the proposed method is faster and more accurate than existing methods, and has lower false alarm rate and better anti-noise performance simultaneously.
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433 China.
authors.forename: Xin
authors.initials: X
authors.lastname: Wang
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433 China.
authors.forename: Qi
authors.initials: Q
authors.lastname: Lv
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433 China ; The Key Laboratory of Wave Scattering and Remote Sensing Information, Fudan University, Shanghai, 200433 China.
authors.forename: Bin
authors.initials: B
authors.lastname: Wang
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433 China.
authors.forename: Liming
authors.initials: L
authors.lastname: Zhang
keywords: Airport detection; Hierarchical discriminant regression (HDR) tree; Hough transform; Saliency map; Scale-invariant feature transform (SIFT); Visual attention