Anti-Excessive Filtering Model Based on Sliding Window

DOI

10.2991/icecee-15.2015.190How to use a DOI?

Keywords

LiDAR; Sliding Window; Anti-Excessive Filtering.

Abstract

This paper is purposed on the problem that ground points in cloud of LiDAR (Light Detection and Ranging) has been excessively filtered. And it proposes an improved model basing on the traditional sliding window model, combining with optimized rules on determining standard elevation value, tolerance of elevation difference and dynamic thresholds. The optimized rules on determining standard elevation could increase the accuracy of filtering, by the nearest neighbor and interpolation algorithm whose theoretical base is spatial correlation. Tolerance of elevation difference prevents excessively filtering by skipping some windows with negligible elevation difference, maintaining the accuracy at a relevant higher level. Dynamic thresholds, changing with various terrains and times of iteration, are adopted to further improve the model based on the mentioned factors. To demonstrate our algorithm and prove its effectiveness, the standard data from ISPRS (International Society for Photogrammetry and Remote Sensing) for testing is selected. Results have shown that both robustness and efficiency increase with the optimization.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Haoang Li
AU  - Weiming Hu
AU  - Jian Yao
AU  - Wenqiao Zhang
PY  - 2015/06
DA  - 2015/06
TI  - Anti-Excessive Filtering Model Based on Sliding Window
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 1002
EP  - 1007
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.190
DO  - 10.2991/icecee-15.2015.190
ID  - Li2015/06
ER  -