基于改进SIFT和SURF算法的沙丘图像配准

唐颖复; 王忠静; 张子雄

doi:10.16511/j.cnki.qhdxxb.2020.22.031

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清华大学学报（自然科学版） ›› 2021, Vol. 61 ›› Issue (2) : 161-169. DOI: 10.16511/j.cnki.qhdxxb.2020.22.031

水利水电工程

基于改进SIFT和SURF算法的沙丘图像配准

唐颖复^1,2, 王忠静^1,3,4, 张子雄¹

作者信息 +

Registration of sand dune images using an improved SIFT and SURF algorithm

TANG Yingfu^1,2, WANG Zhongjing^1,3,4, ZHANG Zixiong¹

Author information +

文章历史 +

摘要

单个沙丘的图像配准受到沙丘图像颜色相近、纹理相似和轮廓模糊等问题困扰，常用的特征提取和特征点配准方法易产生较多的错误匹配点。为了实现有效的单个沙丘跟踪，该文提出了适用于沙丘图像的基于相似三角形原理的尺度不变特征变换（SIFT）和快速鲁棒特征（SURF）的特征点筛选算法。该算法利用暴力匹配法匹配SIFT与SURF特征点，先根据K最近邻算法（KNN）初步筛选匹配点，再利用相似三角形原理对匹配点进一步筛选。将该算法应用于库姆塔格沙漠的沙丘图像配准，实例表明所提出的算法是一种适用性强、准确率高的沙丘图像配准算法。

Abstract

The image registration of a single sand dune is difficult due to the similar colors, similar textures and blurred edges of the dunes. Commonly used methods such as feature extraction and feature point matching tend to have mismatched points. This paper presents an improved feature point screening algorithm with scale invariant feature transform (SIFT) and speeded up robust feature (SURF) based on the similar triangle principle for dune images to improve single sand dune tracking. The algorithm first uses a brutal force method to match the SIFT and SURF feature points, then filters the matching points according to the K nearest neighbor (KNN) algorithm, and finally uses the similar triangle principle to further filter the matching points. This method is then used to register the dunes in the Kumtag desert. The tests show that this algorithm is accurate and can be widely used.

导出引用

唐颖复, 王忠静, 张子雄. 基于改进SIFT和SURF算法的沙丘图像配准[J]. 清华大学学报（自然科学版）. 2021, 61(2): 161-169 https://doi.org/10.16511/j.cnki.qhdxxb.2020.22.031

TANG Yingfu, WANG Zhongjing, ZHANG Zixiong. Registration of sand dune images using an improved SIFT and SURF algorithm[J]. Journal of Tsinghua University(Science and Technology). 2021, 61(2): 161-169 https://doi.org/10.16511/j.cnki.qhdxxb.2020.22.031

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基金

王忠静,教授,E-mail:zj.wang@tsinghua.edu.cn

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2020-07-10	2021-02-15
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