Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds

Hong-chao MA; Jie SUN

doi:10.1631/jzus.C1000235

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Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds

光学工程 | Updated：2022-08-31

- Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds
- Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds
- 信息与电子工程前沿（英文） 2011年12卷第5期页码：417-429
- Affiliations：
  
  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
- Author bio：
  
  E-mail:hchma@whu.edu.cn
- Funds：
- DOI：10.1631/jzus.C1000235
  中图分类号：
- 收稿：2010-07-02，
  
  修回：2011-02-28，
  
  录用：2010-12-13，
  
  纸质出版：2011-05
- Accepted：
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Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds[J]. 信息与电子工程前沿（英文）, 2011,12(5):417-429.

Hong-chao MA, Jie SUN. Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds[J]. Frontiers of Information Technology & Electronic Engineering, 2011, 12(5): 417-429.
Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds[J]. 信息与电子工程前沿（英文）, 2011,12(5):417-429. DOI： 10.1631/jzus.C1000235.

Hong-chao MA, Jie SUN. Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds[J]. Frontiers of Information Technology & Electronic Engineering, 2011, 12(5): 417-429. DOI： 10.1631/jzus.C1000235.

摘要

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.

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