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一种基于形状上下文和HOG特征的异源图像配准方法
Authors
田建东
荣庆轩
黄微
Publication date
14 February 2020
Publisher
Abstract
本发明涉及一种基于形状上下文和HOG特征的异源图像配准方法。针对单模态图像包含的信息存在局限性的问题,提出了一种基于形状上下文和HOG特征的红外和可见光图像配准方法。在混合高斯模型前景检测的基础上,通过提出的形状上下文和HOG特征结合的方法实现轮廓特征匹配,再利用TPS转换模型将匹配延伸到整个形状,并使用正则化和缩放特性迭代重组对应关系及估计转换降低估计误差,最后采用RANSAC算法去除错误匹配点。与已有的形状上下文方法相比,此方法结合了边缘和轮廓特征信息,降低了配准误差,提高了异源图像配准率和配准的鲁棒性
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Last time updated on 16/09/2020