基于模板的前视红外图像建筑物分割方法

摘要

针对前视红外地面建筑物图像目标分割问题,在传统方法的基础上提出了一种基于模板制备的改进C-V模型分割方法.首先通过DSM数据制备目标二维形状模板;然后对图像进行高斯滤波去噪,并采用模板尺度相关的结构元素对图像进行灰度形态学增强;最后引入模板形状先验信息的概念,利用水平集方法表达轮廓先验信息,在C-V模型的基础上增加目标轮廓先验信息能量项,使分割曲线进化同时受到图像数据与形状先验信息驱动,实现目标分割.实测数据显示该方法能在复杂背景条件下精确分割前视红外建筑物目标.%For the question of the segmentation for Forward-looking Infrared (FLIR) building images, a template- based method based on the traditional method is presented. Firstly, the 2D shape templets of building targets are made using the Digital Surface Model (DSM) data. Then, the image is processed by Gaussian filter, and is enhanced using the method of gray-scale mathematic morphology based on template dimension. Furthermore, after the introduction of idea about template shape transcendental information, silhouette information is described using the method of level set. Lastly, the additional energy of target silhouette transcendental information based on the C-V model makes the improvement of segmentation driven by image data and shape transcendental information simultaneity. Finally, target segmentation is realized. Experiment results show the proposed algorithm can precisely segment the buildings from FLIR images with a complicated background.