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

被引：0

作者：

Tang Y. ^{[1
,2
]}

Wang Z. ^{[1
,3
,4
]}

Zhang Z. ^{[1
]}

机构：

[1] Department of Hydraulic Engineering, Tsinghua University, Beijing

[2] China Institute of Water Resources and Hydropower Research, Beijing

[3] State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing

[4] State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining

来源：

Qinghua Daxue Xuebao/Journal of Tsinghua University | 2021年 / 61卷 / 02期

关键词：

Image registration; Remote sensing images; Sand dunes tracking; Scale invariant feature transform (SIFT); Similar triangles; Speeded up robust feature (SURF);

D O I：

10.16511/j.cnki.qhdxxb.2020.22.031

中图分类号：

学科分类号：

摘要：

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. © 2021, Tsinghua University Press. All right reserved.

引用

页码：161 / 169

页数：8

共 27 条

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