一种基于Facet模型的SAR图像特征点检测算法  

A Feature Point Extraction Approach of SAR Image Based on Facet Model

作　　者：黄鹏杰 王宏力 赵爱罡 陆敬辉 姜伟 HUANG Peng-jie WANG Hong-li ZHAO Ai-gang LU Jing-hui JIANG Wei(Department of Control and Engineering, Rocket Force University of Engineering, Xi＇an 710025, China School of Sergeaney, Rocket Force University of Engineering, Qingzhou 262500, China)

机构地区：[1]火箭军工程大学控制工程系,西安710025 [2]火箭军工程大学士官学院,山东青州262500

出　　处：《电光与控制》2017年第1期41-45,共5页Electronics Optics & Control

基　　金：国家自然科学基金(61203189;61374054)

摘　　要：针对SAR图像特征点匹配问题,提出了一种基于Facet模型的特征点检测方法。首先基于Facet模型对局部区域做灰度曲面最佳拟合,然后计算拟合曲面中心点的二阶方向导数,取二阶方向导数极大值小于零的点作为潜在特征点,最后通过对极大值的绝对值归一化和局部非极大值抑制提取特征点。实验结果表明,该算法可有效检测特征点,算法的实时性优于传统的SIFT算法。For the feature point matching of SAR images used in navigation system, a feature point extraction approach is proposed based on Facet model. Firstly, the image intensity surface is well fitted through the Facet model. Then the second-order directional derivative of the center point of the fitting surface is calculated out, and the point whose second-order directional derivative is less than zero is taken as the potential feature point. Through normalization of absolute values for maximum values of the potential feature points and local non-maxima suppression, the feature points are obtained. Experimental results show that the proposed algorithm can successfully detect the feature point, and the real-time performance of the algorithm is better than that of the traditional SIFT algorithm.

关 键 词：合成孔径雷达 特征点提取 FACET模型 二阶方向导数 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]