面向山地区域光照变化下的鲁棒景象匹配方法

doi:10.7527/S1000-6893.2017.321101

电子电气工程与控制

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面向山地区域光照变化下的鲁棒景象匹配方法

王华夏^1,2, 程咏梅¹, 刘楠¹

1. 西北工业大学自动化学院, 西安 710072;
2. 太原科技大学电子信息学院, 太原 030024

收稿日期:2017-01-04 修回日期:2017-03-20 出版日期:2017-10-15 发布日期:2017-03-20
通讯作者: 王华夏 E-mail:wanghx_sam@163.com
基金资助:
国家自然科学基金（61603364）；西安市科技计划项目（CXY1436（9），CXY1350（2））.

A robust scene matching method for mountainous regions with illumination variation

WANG Huaxia^1,2, CHENG Yongmei¹, LIU Nan¹

1. College of Automation, Northwestern Polytechnical University, Xi'an 710072, China;
2. College of Electronic and Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China

Received:2017-01-04 Revised:2017-03-20 Online:2017-10-15 Published:2017-03-20
Supported by:
National Natural Science Foundation of China (61603364);Xi'an Science and Technology Project (CXY1436(9),CXY1350(2))

摘要/Abstract

摘要：

提出了一种面向山地区域光照变化下的鲁棒景象匹配导航方法。该方法针对山区景象匹配导航中光照环境不同造成的基准图与实时图像不一致问题，采取在高程数据上使用光照模型生成光照明暗图，利用数字高程图（DEM）得到水流汇集数据并生成山谷显著图，将光照明暗图与山谷显著图融合作为基准图；针对基准图与实时图中细节边缘的差异带来的误匹配问题，提出了基于形态学约束的Hausdorff距离边缘匹配算法。采用LANDSAT图像与ASTERDEM高程数据进行实验分析，结果表明提出的方法匹配正确率高且鲁棒性好。

关键词: 景象匹配导航, 光照模型, 显著边缘, Hausdorff距离, 图像融合

Abstract:

This paper presents a robust scene matching navigation method for mountainous regions with illumination variation.In order to solve the problem of the inconsistency between the reference map and the real map caused by different lighting conditions in mountainous areas,the reference image is obtained by fusing the hillshade map,generated from elevation data using illumination model,and the valley saliency map,generated from water flow data collected by Digital Elevation Model (DEM).To avoid the mismatch caused by the difference of edge between the reference and the real maps,a Hausdorff distance edge matching algorithm based on morphological constraints is proposed.The experimental results of LANDSAT image and ASTERDEM data show that the proposed method has high accuracy and good robustness.

Key words: scene matching navigation, illumination model, significant edge, Hausdorff distance, image fusion

中图分类号:

V249.32

王华夏, 程咏梅, 刘楠. 面向山地区域光照变化下的鲁棒景象匹配方法[J]. 航空学报, 2017, 38(10): 321101-321101.

WANG Huaxia, CHENG Yongmei, LIU Nan. A robust scene matching method for mountainous regions with illumination variation[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2017, 38(10): 321101-321101.

参考文献

[1] ZHU Z S, SU A, LIU H B, et al. Vision navigation for aircrafts based on 3D reconstruction from real-time image sequences[J]. Science China Technological Sciences, 2015, 58(7):1196-1208.
[2] MANCINI F, DUBBINI M, GATTELLI M, et al. Using unmanned aerial vehicles (UAV) for high-resolution reconstruction of topography:The structure from motion approach on coastal environments[J]. Remote Sensing, 2013, 5(12):6880-6898.
[3] 崔平远, 冯军华, 朱圣英, 等. 基于三维地形匹配的月球软着陆导航方法研究[J]. 宇航学报, 2011, 32(3):470-476. CUI P Y, FENG J H, ZHU S Y, et al. 3D terrain feature matching based navigation for lunar soft landing[J]. Journal of Astronautics, 2011, 32(3):470-476(in Chinese).
[4] 李立春, 苑云, 李由, 等. 三维地形不变性特征描述及其在地形匹配中的应用[J]. 航空学报, 2009, 30(11):2143-2148. LI L C, YUAN Y, LI Y, et al. Invariant feature vector description for 3D terrain and its application to terrain contour matching[J]. Acta Aeronautica et Astronautica Sinica, 2009, 30(11):2143-2148(in Chinese).
[5] LI L C, YU Q F, SHANG Y, et al. A new navigation approach of terrain contour matching based on 3-D terrain reconstruction from onboard image sequence[J]. Science China Technological Sciences, 2010, 53(5):1176-1183.
[6] 马旭, 程咏梅, 郝帅, 等. 面向未知区域深度测量的序列图像稠密点特征生成算法[J]. 航空学报, 2015, 36(2):596-604. MA X, CHENG Y M, HAO S, et al. Dense point feature generation algorithm based on monocular sequence images for depth measurement of unknown zone[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(2):596-604(in Chinese).
[7] SIM D G, PARK R H, KIM R C, et al. Integrated position estimation using aerial image sequences[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(1):1-18.
[8] 于秋则, 程辉, 柳健, 等. 基于改进Hausdorff测度和遗传算法的SAR图像与光学图像匹配[J]. 宇航学报, 2006, 27(1):130-134. YU Q Z, CHENG H, LIU J, et al. Matching SAR image to optical image using modified Hausdorff distance and genetic algorithms[J]. Journal of Astronautics, 2006, 27(1):130-134(in Chinese).
[9] 陈天泽, 李燕. 一种高性能SAR图像边缘点特征匹配方法[J]. 自动化学报, 2013, 39(12):2051-2063. CHEN T Z, LI Y. A high performance edge point feature match method of SAR images[J]. Acta Automatica Sinica, 2013, 39(12):2051-2063(in Chinese).
[10] WANG T, CELIK K, SOMANI A K. Characterization of mountain drainage patterns for GPS-denied UAS navigation augmentation[J]. Machine Vision and Applications, 2016, 27(1):87-101.
[11] WANG L, LIU H. An efficient method for identifying and filling surface depressions in digital elevation models for hydrologic analysis and modelling[J]. International Journal of Geographical Information Science, 2006, 20(2):193-213.
[12] HUTTENLOCHER D P, KLANDERMAN G A, RUCKLIDGE W J. Comparing images using the Hausdorff distance[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1993, 15(9):850-863.
[13] DUBUISSON M P, JAIN A K. A modified Hausdorff distance for object matching[C]//Proceedings of 12th International Conference on Pattern Recognition, 1994:566-568.
[14] SIM D G, KWON O K, PARK R H. Object matching algorithms using robust Hausdorff distance measures[J]. IEEE Transactions on Image Processing, 1999, 8(3):425-429.
[15] KWON O K, KIM D, SUH J W. Accurate M-Hausdorff distance similarity combining distance orientation for matching multi-modal sensor images[J]. Pattern Recognition Letters, 2011, 32(7):903-909.
[16] LOPEZ A M, LLORET D, SERRAT J, et al. Multilocal creaseness based on the level-set extrinsic curvature[J]. Computer Vision and Image Understanding, 2000, 77(2):111-144.
[17] CANNY J. A computational approach to edge detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986(6):679-698.
[18] CHEN H F, BELHUMEUR P N, JACOBS D W. In search of illumination invariants[C]//IEEE Conference on Computer Vision and Pattern Recognition,2000:254-261.
[19] HOM B. Robot vision[M]. Beijing:China Youth Press, 2014:246-247.
[20] BONHAM-CARTER G F. Geographic information systems for geoscientists:Modelling with GIS[M]. Amsterdam:Elsevier, 2014:295-297.
[21] JENSON S K, DOMINGUE J O. Extracting topographic structure from digital elevation data for geographic information system analysis[J]. Photogrammetric Engineering and Remote Sensing, 1988,54(11):1593-1600.

E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

面向山地区域光照变化下的鲁棒景象匹配方法

A robust scene matching method for mountainous regions with illumination variation

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