Signal and Information Processing

Least Square Image Matching Algorithm Considering Elevation Plane and Parallax Constraints

Expand
  • 1. College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China;
    2. State Key Laboratory of Information Engineering in Surveying, Mapping & Remote Sensing, Wuhan University, Wuhan 430079, China

Received date: 2017-09-18

  Revised date: 2017-11-21

  Online published: 2018-09-30

Abstract

Aiming at the problem that the traditional least square image matching algorithm is limited by the image quality and the initial condition, this paper proposes a least square image matching algorithm considering elevation plane and parallax constraints by means of combining the characteristics of the vertical line locus and the multi-slice least square matching algorithm based on collinear constraints. The algorithm is based on elevation plane constraint matching where the parallax constraint is used in searching and matching process. The parallax offset can provide reliable and stable initial condition for the least square matching, realizing precisely matching of images. There experiments are conducted with the vertical line locus method, the multi-slice least square matching algorithm with collinear conditional constraints and with the proposed algorithm, respectively.Experimental results proof that the proposed algorithm has obvious advantages in matching accuracy and subsequent calculation of aerial triangulation, compard with the other two algorithms.

Cite this article

ZHANG Chun-sen, MU Yan, ZHU Shi-huan, GUO Bing-xuan, QIU Zhen-guo . Least Square Image Matching Algorithm Considering Elevation Plane and Parallax Constraints[J]. Journal of Applied Sciences, 2018 , 36(5) : 826 -836 . DOI: 10.3969/j.issn.0255-8297.2018.05.010

References

[1] 李德仁,李明. 无人机遥感系统的研究进展与应用前景[J]. 武汉大学学报(信息科学版),2014, 39(5):505-513. Li D R, Li M. Research advance and application prospect of unmanned aerial vehicle remote sensing system[J]. Geomatics and Information Science of Wuhan University, 2014, 39(5):505-513. (in Chinese)
[2] 袁修孝,高宇,邹小容. GPS辅助空中三角测量在低空航测大比例尺地形测图中的应用[J]. 武汉大学学报(信息科学版),2012, 37(11):1289-1293. Yuan X X, Gao Y, Zou X R. Application of GPS-supported aerotriangulation in large scale topographic mapping based on low-altitude photogrammetry[J]. Geomatics and Information Science of Wuhan University, 2012, 37(11):1289-1293. (in Chinese)
[3] 张永生. 现场直播式地理空间信息服务的构思与体系[J]. 测绘学报,2011, 40(1):1-4. Zhang Y S. The conception and architecture of live-service for geospatial information[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(1):1-4. (in Chinese)
[4] 毕凯,李英成,丁晓波,刘飞. 轻小型无人机航摄技术现状及发展趋势[J]. 测绘通报,2015(3):27-31. Bi K, Li Y C, Ding X B, Liu F. Aerial photogrammetric technology of light small UAV:status and trend of development[J]. Bulletin of Surveying and Mapping, 2015(3):27-31. (in Chinese)
[5] 李德仁,肖雄武,郭丙轩. 倾斜影像自动空三及其在城市真三维模型重建中的应用[J]. 武汉大学学报(信息科学版),2016, 41(6):711-721. Li D R, Xiao X W, Guo B X. Oblique image based automatic aerotriangulation and its application in 3D city model reconstruction[J]. Geomatics and Information Science of Wuhan University, 2016, 41(6):711-721. (in Chinese)
[6] 杨爱玲,于洪伟,郑灿辉. 关于轻型无人机航摄影像的质量探讨[J]. 测绘与空间地理信息,2011, 34(2):185-187. Yang A L, Yu H W, Zheng C H. Quality discussion on the aerial image of light UAV[J]. Geomatics & Spatial Information Technology, 2011, 34(2):185-187. (in Chinese)
[7] 张剑清,潘励,王树根. 摄影测量学:2版[M]. 武汉:武汉大学出版社,2009.
[8] 范大昭,纪松,张永生. 物方多视匹配算法的严密投影辐射线模型[J]. 测绘科学,2014, 39(9):7-10. Fan D Z, Ji S, Zhang Y S. Research on rigorous projection line of object space multi-view matching model[J]. Science of Surveying and Mapping, 2014, 39(9):7-10. (in Chinese)
[9] 董莉,李浩,佟光成. VLL影像匹配的线路地形断面测绘方法[J]. 测绘科学,2013, 38(4):101-103. Dong L, Li H, Tong G C. Route section survey method based on VLL image matching[J]. Science of Surveying and Mapping, 2013, 38(4):101-103. (in Chinese)
[10] 齐润冰,宋伟东. 物方多视影像密集匹配方法[J]. 测绘科学,2015, 40(10):98-101. Qi R B, Song W D. A dense matching algorithm of multi-view image based on the object space[J]. Science of Surveying and Mapping, 2015, 40(10):98-101. (in Chinese)
[11] 杨楠,邵振峰,郭丙轩. 非固定初始面元的无人机影像点云优化算法[J]. 武汉大学学报(信息科学版),2016, 41(8):1013-1020. Yang N, Shao Z F, Guo B X. Point cloud optimization for UAV image based on non-fixed initial patch[J]. Geomatics and Information Science of Wuhan University, 2016, 41(8):1013-1020. (in Chinese)
[12] Baltsavias E P. Multiphoto geometrically constrained matching[J]. Mitteilungen, 1991:49.
[13] Rosenholm D. Multi-point matching using the least squares technique for evaluation of threedimensionl models[J]. Photogrammetric Engineering and Remote Sensing, 1987, 53(6):621-626.
[14] 陈晓辉, 马丽霞, 王晓光. 基于像方特征点的多视影像最小二乘匹配[J]. 测绘与空间地理信息, 2013, 36(10):248-254. Chen X H, Ma L X, Wang X G. The least-square matching of multi-view images based on photographical feature points[J]. Geomatics & Spatial Information Technology, 2013, 36(10):248-254. (in Chinese)
[15] 王竞雪,朱庆,王伟玺. 多匹配基元集成的多视影像密集匹配方法[J]. 测绘学报,2013, 42(5):691-698. Wang J X, Zhu Q, Wang W X. A dense matching algorithm of multi-view image based on the integrated multiple matching primitives[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(5):691-698. (in Chinese)
[16] Helava. Object space least-squares correlation[J]. Photogrammetric Engineering and Remote Sensing, 1988, 54(6):711-714.
[17] 张祖勋,张剑清. 数字摄影测量学[M]. 武汉:武汉大学出版社,2002.
[18] Harris C G, Stephens M J. A combined corner and edge detector[C]//Processing Fourth Alley Vision Conference, Manchester, 1988:147-151.
[19] Lowe D G. Object recognition from local scale-invariant features[C]//Proceeding of the International Conference on Computer Vision, 1999:1150-1157.
[20] Lowe D G. Distinctive image features from scale-invariant key points[J]. International Journal of Computer Vision, 2004, 60(2):91-110.
Outlines

/