期刊
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 10, 期 3, 页码 573-577出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2012.2214022
关键词
Aircraft recognition; image segmentation; level set method; shape prior; template matching
类别
资金
- National Natural Science Foundation of China [41001285]
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.
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