融合Harris-Laplace算子的SURF算法与无人机影像匹配A SURF algorithm combined with Harris-Laplace and UAV images matching
蔡香玉,盛业华,黄毅,张卡,吕海洋
摘要(Abstract)：
针对传统的SURF算法在尺度、旋转和模糊变化方面具有一定的稳定性,运算相对较快,但匹配正确率不理想的问题,该文提出结合Harris-Laplace算子与Hessian矩阵的优点在多尺度下提取影像上的特征点,设定较严格阈值约束提取出显著的特征点。将这些特征点进行特征描述,并作为候选匹配点,取较严格的比率阈值,用欧式距离比值法进行特征点匹配。结果表明,使用本文的算法对无人机倾斜影像进行了成功匹配,不仅获取较多的匹配点,提高了匹配的正确率,而且运算时间与传统SURF算法相当,增强了不同类型影像的适应性和稳健性。
关键词(KeyWords)： 低空无人机摄影;影像匹配;特征点提取;SURF算法;Harris-Laplace算子
基金项目(Foundation): 国家自然科学基金项目(41631175,41471102);; 江苏省自然科学基金项目(BK20151547);; 江苏高校优势学科建设工程资助项目
作者(Author): 蔡香玉,盛业华,黄毅,张卡,吕海洋
DOI: 10.16251/j.cnki.1009-2307.2018.11.004
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