高分辨率遥感图像SIFT和SURF算法匹配性能研究 -

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高分辨率遥感图像SIFT和SURF算法匹配性能研究

doi:10.3788/CO.20171003.0331

1.
中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
2.
中国科学院大学, 北京 100049

基金项目:

国家自然科学基金资助项目61405191

详细信息

作者简介:
齐冰洁(1991-), 女, 辽宁开原人, 硕士研究生, 主要从事遥感图像处理方面的研究。E-mail:doudouqbj@126.com
刘金国(1968—)，男，吉林蛟河人，硕士，研究员，硕士生导师，主要从事空间遥感与图像处理方面的研究。E-mail:liujg@ciomp.ac.cn

通讯作者:
刘金国, E-mail:liujg@ciomp.ac.cn

中图分类号:TP391
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- 被引次数:0
出版历程
- 收稿日期:2017-01-18
- 修回日期:2017-03-27
- 刊出日期:2017-06-01

Research on matching performance of SIFT and SURF algorithms for high resolution remote sensing image

1.
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China

Funds:

National Natural Science Foundation of China61405191

摘要

摘要:遥感图像匹配是图像校正、拼接的基础。由于遥感图像特征相似度大，重叠区域小，遥感图像对匹配算法的要求更高。本文首先从特征检测、特征描述和特征匹配三个方面，比较了SIFT算法和SURF算法在计算速度和准确度方面性能，然后研究了算法对遥感图像重叠度、度量距离的要求，并针对SURF算法对特征方向误差敏感的特点，提出一种oSURF算法；最后利用卫星1A级条带遥感图像分析各个算法优劣性。测试结果表明，相比于SIFT算法，SURF算法计算速度为SIFT的3倍，需要的图像重叠宽度仅为1.25倍描述向量尺寸，而在保证同样匹配率的情况下，SIFT算法则需要图像重叠宽度为1.5倍描述向量尺寸。本文提出的oSURF算法在保证计算速度的同时，准确度相对于SURF算法提升5%~10%，因此，oSURF算法更适合1A级条带遥感图像的拼接。
- 遥感图像/
- 特征匹配/
- SIFT/
- SURF/
- 重叠度
Abstract:Image matching is the basis of image rectification and mosaic. Because of higher features similarity and smaller overlapped area than ordinary images, the remote sensing images have higher requirements on matching algorithm in both performance and iteration speed. The performances in three aspects:feature detection, feature description and feature matching, are analyzed between the SIFT algorithm and the SURF algorithm in terms of speed and accuracy. The requirements of the degree of overlapping between remote sensing images and the matching distance of the genvector is discussed as well. In view of the characteristic that SURF algorithm is sensitive to the error in feature detection, oSURF algorithm is presented in this paper. Finally, the advantages and disadvantages of each algorithm are analyzed by using satellite remote sensing data of level 1A. The results show that iteration speed of SURF algorithm is three times faster than SIFT algorithm. Under the same matching rate, the width of overlapped area on image required in SURF algorithm is 1.25 times of the dimension of genvector but 1.5 times in SIFT, and the accuracy of oSURF algorithm is increased by 5%~10% compared with SURF algorithm in the same computation speed, which indicate that oSURF is more suitable for remote sensing image stitching.
- remote sensing image/
- feature matching/
- SIFT/
- SURF/
- degree of overlapping

HTML全文

图 1美国某海岸影像数据

Figure 1.Image of an America′s shore

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图 2SIFT和SURF算法特征点检测效果

Figure 2.Detection result of SIFT and SURF algorithm

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图 3检测区域宽度不同时描述向量个数变化

Figure 3.Vector number change with the detection area

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图 4重叠区域不同时同名点概率变化

Figure 4.Probability change of Homologous Points with the overlap region

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图 5不同算法匹配效果图

Figure 5.Matching result of different algorithms

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图 6非重叠区域的影响

Figure 6.Influence of non-overlapping domain

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图 7不同算法计算距离不同时正确率的变化情况

Figure 7.Matching ratio change with the calculated distance

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图 8Haar小波滤波器

Figure 8.Haar wavelet filters

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图 9扇形窗口

Figure 9.Sector window

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图 10oSURF算法匹配效果图

Figure 10.Matching result of oSURF algorithm

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图 11不同算法匹配结果

Figure 11.Matching result of different algorithms

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表 1SIFT和SURF算法特征检测结果

Table 1.Detection result of SIFT and SURF algorithm

图像	算法	特征点数/个	检测时间/s
条带图像1	SIFT	438	5.013
	SURF	523	1.596
条带图像2	SIFT	480	5.326
	SURF	573	1.869

下载: 导出CSV

表 2不同算法特征向量描述结果

Table 2.Feature description result of different algorithms

算法	图像	特征向量	特征点变化	描述时间	10个向量描述时间
SIFT	条带图像1	1 119	+681	12.962	0.116
	条带图像2	1 451	+971	13.863	0.096
SURF64	条带图像1	464	-59	3.015	0.065
	条带图像2	520	-53	3.368	0.065
SURF128	条带图像1	464	-59	3.213	0.069
	条带图像2	520	-53	3.473	0.067

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表 3不同算法特征匹配结果比较

Table 3.Matching result of different algorithms

算法	匹配点	正确率	匹配时间	总时间
SIFT	286	0.979	1.152	38.521
SURF64	84	0.896	0.310	11.514
SURF128	120	0.946 7	0.425	12.581

下载: 导出CSV

表 4oSURF算法特征匹配结果比较

Table 4.Matching result of oSURF algorithm

算法	条带1描述向量	条带2描述向量	匹配点数	准确度	总时间
oSURF	814	963	289	0.965 4	12.926

下载: 导出CSV

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