Please wait a minute...
FITEE
Front. Inform. Technol. Electron. Eng.  2011, Vol. 12 Issue (5): 417-429    DOI: 10.1631/jzus.C1000235
    
Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds
Hong-chao Ma*,1, Jie Sun2
1 School of Remote Sensing, Wuhan University, Wuhan 430079, China 2 State Key Lab for Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds
Hong-chao Ma*,1, Jie Sun2
1 School of Remote Sensing, Wuhan University, Wuhan 430079, China 2 State Key Lab for Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
 全文: PDF(1035 KB)  
摘要： A detailed study was carried out to find optimal seam-lines for mosaicking of images acquired by an airborne light detection and ranging (LiDAR) system. High ground objects labeled as obstacles can be identified by delineating black holes from filtered point clouds obtained by filtering the raw laser scanning dataset. An innovative A* algorithm is proposed that can automatically make the seam-lines keep away from these obstacles in the registered images. This method can intelligently optimize the selection of seam-lines and improve the quality of orthophotos. A simulated grid image was first used to analyze the effect of different heuristic functions on path planning. Three subsets of LiDAR data from Xi’an, Dunhuang, and Changyang in Northwest China were obtained. A quantitative method including pixel intensity, hue, and texture was used. With our proposed method, 9.4%, 8.7%, and 9.8% improvements were achieved in Dunhuang, Xi’an, and Changyang, respectively.
关键词： Light detection and ranging (LiDAR);  Filter;  A* algorithm;  Mosaicking;  Seam-line    
Abstract: A detailed study was carried out to find optimal seam-lines for mosaicking of images acquired by an airborne light detection and ranging (LiDAR) system. High ground objects labeled as obstacles can be identified by delineating black holes from filtered point clouds obtained by filtering the raw laser scanning dataset. An innovative A* algorithm is proposed that can automatically make the seam-lines keep away from these obstacles in the registered images. This method can intelligently optimize the selection of seam-lines and improve the quality of orthophotos. A simulated grid image was first used to analyze the effect of different heuristic functions on path planning. Three subsets of LiDAR data from Xi’an, Dunhuang, and Changyang in Northwest China were obtained. A quantitative method including pixel intensity, hue, and texture was used. With our proposed method, 9.4%, 8.7%, and 9.8% improvements were achieved in Dunhuang, Xi’an, and Changyang, respectively.
Key words: Light detection and ranging (LiDAR)    Filter    A* algorithm    Mosaicking    Seam-line
收稿日期: 2010-07-02 出版日期: 2011-05-09
CLC:  P237.3  
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章　　
Hong-chao Ma
Jie Sun

引用本文:

Hong-chao Ma, Jie Sun. Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds. Front. Inform. Technol. Electron. Eng., 2011, 12(5): 417-429.

链接本文:

http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C1000235    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2011/V12/I5/417

[1] Qun-wei XU, Jin-xiang ZHAN, Long XIAO, Guo-zhu CHEN. A multi-modular shunt active power filter system and its novel fault-tolerant strategy based on split-phase control and real-time bus communication[J]. Front. Inform. Technol. Electron. Eng., 2018, 19(9): 1166-1179.
[2] Zhi-hua LU, Meng-yao ZHU, Qing-wei YE, Yu ZHOU. Performance analysis of two EM-based measurement bias estimation processes for tracking systems[J]. Front. Inform. Technol. Electron. Eng., 2018, 19(9): 1151-1165.
[3] Che LIN, Rong-hao ZHENG, Gang-feng YAN, Shi-yuan LU. Convergence analysis of distributed Kalman filtering for relative sensing networks[J]. Front. Inform. Technol. Electron. Eng., 2018, 19(9): 1063-1075.
[4] Muhammad Asif Zahoor RAJA, Muhammad Saeed ASLAM , Naveed Ishtiaq CHAUDHARY. Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification of secondary path[J]. Front. Inform. Technol. Electron. Eng., 2018, 19(2): 246-259.
[5] Jian-zhi LI , Bo AI , Rui-si HE , Qi WANG , Mi YANG , Bei ZHANG , Ke GUAN , Dan-ping HE , Zhang-dui ZHONG , Ting ZHOU , Nan LI. Indoor massive multiple-input multiple-output channel characterization and performance evaluation[J]. Front. Inform. Technol. Electron. Eng., 2017, 18(6): 773-787.
[6] Wei ZHANG , Jia-yu ZHUANG , Xi YONG , Jian-kou LI , Wei CHEN , Zhe-min LI. Personalized topic modeling for recommending user-generated content[J]. Front. Inform. Technol. Electron. Eng., 2017, 18(5): 708-718.
[7] Wei LIU, Ai-qun HU. A subband excitation substitute based scheme for narrowband speech watermarking[J]. Front. Inform. Technol. Electron. Eng., 2017, 18(5): 627-643.
[8] Jun-sheng LV, You LI , Yu-mei ZHOU , Jian-zhong ZHAO , Hai-hua SHEN , Feng ZHANG. Wide-range tracking technique for process-variation-robust clock and data recovery applications[J]. Front. Inform. Technol. Electron. Eng., 2017, 18(5): 729-737.
[9] Yong-ping DU, Chang-qing YAO , Shu-hua HUO, Jing-xuan LIU. A new item-based deep network structure using a restricted Boltzmann machine for collaborative filtering[J]. Front. Inform. Technol. Electron. Eng., 2017, 18(5): 658-666.
[10] Zhao-yun CHEN, Lei LUO, Da-fei HUANG, Mei WEN, Chun-yuan ZHANG. Exploiting a depth context model in visual tracking with correlation filter[J]. Front. Inform. Technol. Electron. Eng., 2017, 18(5): 667-679.
[11] Ke JIN, Tao LAI, Gong-quan LI, Ting WANG, Yong-jun ZHAO . Ultra-wideband FMCW ISAR imaging with a large rotation angle based on block-sparse recovery[J]. Front. Inform. Technol. Electron. Eng., 2017, 18(12): 2058-2069.
[12] Tian-cheng LI, Jin-ya SU, Wei LIU, Juan M. CORCHADO. Approximate Gaussian conjugacy: parametric recursive filtering under nonlinearity, multimodality, uncertainty, and constraint, and beyond[J]. Front. Inform. Technol. Electron. Eng., 2017, 18(12): 1913-1939.
[13] Tao LI, Jun WANG, Hao LIU, Li-gang LIU. Efficient mesh denoising via robust normal filtering and alternate vertex updating[J]. Front. Inform. Technol. Electron. Eng., 2017, 18(11): 1828-1842.
[14] Jing WANG, Lan-fen LIN, Heng ZHANG, Jia-qi TU, Peng-hua YU . A novel confidence estimation method for heterogeneous implicit feedback[J]. Front. Inform. Technol. Electron. Eng., 2017, 18(11): 1817-1827.
[15] Ji-zhou LUO, Sheng-fei SHI, Hong-zhi WANG, Jian-zhong LI. FrepJoin: an efficient partition-based algorithm for edit similarity join[J]. Front. Inform. Technol. Electron. Eng., 2017, 18(10): 1499-1511.