Share Email Print
cover

Proceedings Paper

An improved 1D filtering method for LIDAR point cloud
Author(s): Jing Zhang; Fang Zhang; Wanshou Jiang; Xiaojun Zhang; Lelin Li; Jianchao Wang; Dahai Guo
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

This paper discusses how to separate non-ground points from raw LIDAR point cloud. For the purpose of improving processing efficiency and precision, an improved 1-D filtering method is proposed. The entire filtering process is divided into eight steps and non-ground points are eliminated progressively. In these processing steps, a key-point detection technique is used to segment points in profile. Based on these profile segments, detailed analysis is utilized to implement segment-oriented filtering innovatively. This method makes use of entire features of segmental points for classification, so it is more accuracy and robust than traditional point-by-point classification. Two different scale datasets are used to test our method. Compared to 1-D labeling method, the proposed method is more effective and efficiency.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 74941S (30 October 2009); doi: 10.1117/12.832820
Show Author Affiliations
Jing Zhang, Wuhan Univ. (China)
Fang Zhang, Wuhan Univ. (China)
Wanshou Jiang, Wuhan Univ. (China)
Xiaojun Zhang, Wuhan Univ. (China)
Lelin Li, Wuhan Univ. (China)
Jianchao Wang, Aero Geophysical Survey & Remote Sensing Ctr. (China)
Dahai Guo, Aero Geophysical Survey & Remote Sensing Ctr. (China)


Published in SPIE Proceedings Vol. 7494:
MIPPR 2009: Multispectral Image Acquisition and Processing

© SPIE. Terms of Use
Back to Top