一种适合于大尺寸航拍图像的特征点提取方法
收稿日期: 2013-04-07
修回日期: 2013-06-28
网络出版日期: 2013-07-12
基金资助
国家自然科学基金（61170185）；辽宁省科技攻关计划项目（2011217002）
A Feature Point Extraction Method for Large Size Aerial Images
Received date: 2013-04-07
Revised date: 2013-06-28
Online published: 2013-07-12
Supported by
National Natural Science Foundation of China (61170185);Scientific and Technological Research Projects in Liaoning (2011217002)
石祥滨 , 张劲松 , 陈润锋 , 刘进立 . 一种适合于大尺寸航拍图像的特征点提取方法[J]. 航空学报, 2014 , 35(1) : 240 -248 . DOI: 10.7527/S1000-6893.2013.0326
The existing feature point extraction methods usually cost a lot of CPU time when they are applied to large size aerial images. For the purpose of fast extraction of feature points in these large size aerial images, a novel method is developed. Usually these aerial images have not only large sizes but also wide ranges of shooting. They usually have different feature point performances on different scales and the distributions of spectra are uniform in the frequency domain. In this paper, the scales of the feature points are kept by employing the Laplacian pyramid, and a specified non-uniform N-dimensional directional filter bank is applied to decompose the pyramid images. The scales and the directions of the images are extracted. Then the local extreme points are extracted as a candidate feature points set. Finally, the candidate feature points in different directions are merged by a specified merge-strategy. Thus, we obtain the final feature points set and the directions of the feature point described by the direction filter bank. Experimental results are presented that demonstrate the proposed method is efficient for large size aerial images while meeting the match rate and precision rate requirements.
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