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Remote Sens. 2016, 8(1), 35;

An Improved Morphological Algorithm for Filtering Airborne LiDAR Point Cloud Based on Multi-Level Kriging Interpolation

Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China
Author to whom correspondence should be addressed.
Academic Editors: Diego Gonzalez-Aguilera, Fabio Remondino, Magaly Koch, Nicola Masini and Prasad S. Thenkabail
Received: 28 October 2015 / Revised: 16 December 2015 / Accepted: 29 December 2015 / Published: 5 January 2016
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Filtering is one of the core post-processing steps for airborne LiDAR point cloud. In recent years, the morphology-based filtering algorithms have proven to be a powerful and efficient tool for filtering airborne LiDAR point cloud. However, most traditional morphology-based algorithms have difficulties in preserving abrupt terrain features, especially when using larger filtering windows. In order to suppress the omission error caused by protruding terrain features, this paper proposes an improved morphological algorithm based on multi-level kriging interpolation. This algorithm is essentially a combination of progressive morphological filtering algorithm and multi-level interpolation filtering algorithm. The morphological opening operation is performed with filtering window gradually downsizing, while kriging interpolation is conducted at different levels according to the different filtering windows. This process is iterative in a top to down fashion until the filtering window is no longer greater than the preset minimum filtering window. Fifteen samples provided by the ISPRS commission were chosen to test the performance of the proposed algorithm. Experimental results show that the proposed method can achieve promising results not only in flat urban areas but also in rural areas. Comparing with other eight classical filtering methods, the proposed method obtained the lowest omission error, and preserved protruding terrain features better. View Full-Text
Keywords: point cloud; morphology; filtering; multi-level; kriging interpolation point cloud; morphology; filtering; multi-level; kriging interpolation

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Hui, Z.; Hu, Y.; Yevenyo, Y.Z.; Yu, X. An Improved Morphological Algorithm for Filtering Airborne LiDAR Point Cloud Based on Multi-Level Kriging Interpolation. Remote Sens. 2016, 8, 35.

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