【摘要】 图像配准技术是近些年来图像处理领域发展迅速的研究方向之一.在遥感领域内,图像配准更是实现图像融合、运动检测、图像校正、图像拼接等应用的一个关键步骤.尽管国内外目前在图像配准方面提出了很多方法,但不同方法适用的图像范围不同,很多时候需要人工干预进行方法的选择.尤其对于无人机这种快速、实时获取图像的新型遥感平台,如何集合不同方法的优点以实现图像自动配准成为了关键性问题.本文在比较分析了基于SIFT和SURF特征提取图像配准方法的各自优势后,提出基于几何矩的方法对图像进行预先分类,从而决定将其分配给何种方法进行配准,实现全程自动化.实验证明,这种图像自动配准方法在拓宽了图像应用范围的同时保证了良好的配准效果.更多还原

【Abstract】 Recently,image registration technology is one of the rapid development field in image processing area.In remote sensing field,it is a significant step for image fusion,moving detection,image correction,image mosaic and so on.Although there are many methods for image registration in the world,different methods apply to different kinds of images,most time the methods are selected by human intervening but not automatically.It becomes a key issue that how to combine the advantages of different methods to achieve automatic image registration,especially for UAV images.In this paper,a pre-classifying method based on geometric moment is proposed after the comparison of image registration methods based on SIFT and SURF feature extraction,in order to decide which image registration method is the best one,thereby,achieve the whole automatic process.The experiments show that this automatic image registration method makes sure a good matching effect and at the same time it broaden the types of applicative images.更多还原