A Study of a Denoising Method for Three Dimensional Data Based on Mean Shift

Author

Yu, Fenghua ; Lai, Xudong

Author_Institution

Sch. of RSIE, Wuhan Univ., Wuhan, China

fYear

2011

fDate

14-17 Dec. 2011

Firstpage

39

Lastpage

42

Abstract

LiDAR is a kind of remote sensing technology with a big development in recent years. It attracts much attention because of the rapid access of the three dimensional coordinates. But the model built from the LiDAR data includes noise inevitably. How to remove the noise to improve the quality of three dimensional models becomes a problem which can not be ignored. This paper does a research on the principles of Mean Shift method. The experimental thresholds were calculated after three dimensional data smoothing, and then denoise. Finally there are results of different data.

Keywords

optical radar; remote sensing; signal denoising; LiDAR data; denoising method; light detection and ranging; mean shift method; remote sensing technology; three dimensional coordinates; three dimensional data smoothing; three dimensional models; Educational institutions; Filtering theory; Kernel; Laser radar; Low pass filters; Noise; Smoothing methods; Denoise; LiDAR; Mean Shift; Threshold;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation and Bio-Medical Instrumentation (ICBMI), 2011 International Conference on

Conference_Location

Wuhan, Hubei

Print_ISBN

978-1-4577-1152-7

Type

conf

DOI

10.1109/ICBMI.2011.41

Filename

6131699