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

doi:10.16511/j.cnki.qhdxxb.2020.22.031

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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.

Keywords sand dunes tracking remote sensing images scale invariant feature transform (SIFT) speeded up robust feature (SURF) image registration similar triangles

Issue Date: 29 December 2020

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	TANG Yingfu
	WANG Zhongjing
	ZHANG Zixiong

Cite this article:

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.

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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2020.22.031 OR http://jst.tsinghuajournals.com/EN/Y2021/V61/I2/161

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