水平集分割方法在合成孔径雷达图像目标识别中的应用

正确分割目标、提取目标的有效特征是合成孔径雷达图像目标识别中的一个关键问题。将水平集图像分割方法应用于合成孔径雷达图像目标识别，将目标图像中的目标区和阴影区从背景杂波中分割出来，其中目标区的形状作为目标的有效特征用于基于模板匹配的目标识别中。用MSTAR数据库中的3类目标的图像数据对该方法进行验证和分析，实验结果表明，在基于模板匹配的目标识别中，该分割方法可提取出有效的目标形状特征，实现目标的正确识别。 

Target Recognition of Synthetic Aperture Radar Images Using Level-Set Segmentation Method

Correct segmentation and effective feature extraction is a critical problem in target recognition of synthetic aperture radar images.In this paper,level-set method was applied in target recognition of synthetic aperture radar images.Target and shadow regions of each image were segmented from background clutter regions using level-set method.The shape of target region was used as significant feature in target recognition based on template matching.Image samples of three targets in MSTAR database are used to verify the method.The results show that using level-set segmentation and template matching can extract effective feature of target and achieve correct recognition of targets.