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Aircraft Recognition in High-Resolution Satellite Images Using Coarse-to-Fine Shape Prior

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4 Author(s)
Ge Liu ; Key Lab. of Technol. in Geo-spatial Inf. Process. & Applic. Syst., Beijing, China ; Xian Sun ; Kun Fu ; Hongqi Wang

Automatic aircraft recognition in high-resolution satellite images has many important applications. Due to the diversity and complexity of fore-/background, recognition using pixel-based methods usually does not perform well. In this letter, we propose a new method integrating the high-level information of a shape prior, which is considered as a coarse-to-fine process. In the coarse stage, the pose of an aircraft is roughly estimated by a single template matching with a defined score criterion. In the fine stage, we derive a parametric shape model by applying principal component analysis and kernel density function, which have good effects on both dimension reduction and sample space description; then, a new variational formulation combining region information and a shape prior is proposed to segment the object using a level set method. Finally, the parameters of the segmentation result are directly applied to verify aircraft type with two k-nearest neighbor steps. Experiments on QuickBird images demonstrate the robustness and accuracy of the proposed method.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:10 ,  Issue: 3 )