摘要
基于无下采样Contourlet变换(NSCT)在图像分解方面的优势,结合改进SIFT算法,提出了一种对遥感图像进行配准的方法。首先,使用NSCT将参考图像和待匹配图像进行分解,获取遥感图像的低频图像;其次,采用Canny边缘检测得到图像的边缘坐标点,与SIFT算法所获取的图像关键点的坐标比对,去除不稳定的响应点后,得到优化后的匹配点对;最后,对错误匹配点用RANSAC算法提纯。试验研究表明:本文算法可以减少使用单SIFT算法对遥感图像匹配的时间,提高匹配精度,可行且有效。
Based on the advantage of non-subsampling contourlet transform （NSCT） in image decomposition and improved SIFT algnrithm,a new method of registering remote sensing inmges is proposed in this paper. First, the remote sensing image to be matched and the reference image are decomposed by NSCT.Two low-frequency images of remote sensing images are acquired.Secondly,the Canny edge detection is used to require the edge coordinates of image, this points is contrasted with the coordinates of the key points detect by SIFT which can remove some unstable response points. Finally, use the RANSAC algorithm to remove the wrong point, the rest of the points are used to match remote sensing images. The experimental Results show that the new method can efficiently decrease remote sensing image matching time by only use SIFT algorithm and increase the accuracy of remote sensing image matching.
作者
宋佳乾
汪西原
SONG Jiaqian;WANG Xiyuan(School of Physics and Electronic-Electrical Engineering,Ningxia University,Yinehuan 750021,China)
出处
《测绘通报》
CSCD
北大核心
2018年第9期34-38,共5页
Bulletin of Surveying and Mapping
基金
国家自然科学基金(41561087)
