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Journal ArticleDOI

Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds

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TLDR
In general, filters that estimate local surfaces are found to perform best and should be directed towards the usage of additional data sources, segment-based classification, and self-diagnosis of filter algorithms.
Abstract
Over the past years, several filters have been developed to extract bare-Earth points from point clouds. ISPRS Working Group III/3 conducted a test to determine the performance of these filters and the influence of point density thereon, and to identify directions for future research. Twelve selected datasets have been processed by eight participants. In this paper, the test results are presented. The paper describes the characteristics of the provided datasets and the used filter approaches. The filter performance is analysed both qualitatively and quantitatively. All filters perform well in smooth rural landscapes, but all produce errors in complex urban areas and rough terrain with vegetation. In general, filters that estimate local surfaces are found to perform best. The influence of point density could not well be determined in this experiment. Future research should be directed towards the usage of additional data sources, segment-based classification, and self-diagnosis of filter algorithms.

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Citations
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Proceedings ArticleDOI

Hybrid filtering of Lidar Data based on the Echoes

TL;DR: A new algorithm called Hybrid Filtering of Lidar Data based on the Echoes was proposed, which can reduce the amount of computing data, but also improve the effect of filtering algorithm for eliminating the building and vegetation.
Journal ArticleDOI

A Progressive Plane Detection Filtering Method for Airborne LiDAR Data in Forested Landscapes

Shangshu Cai, +2 more
- 02 Mar 2023 - 
TL;DR: In this paper , a progressive plane detection filtering (PPDF) method was proposed for ground filtering in airborne light detection and ranging (LiDAR) point clouds for forestry applications.
Journal Article

Detection of Ground in Point-clouds Generated from Stereo-pair Images

TL;DR: This paper proposes a new approach for constructing digital terrain models (DTM) from the point-clouds generated from airborne stereo-pair images that uses data decomposition based on the differential attribute profiles and -mapping for the extraction of the most-contrasted connected-components.
Proceedings ArticleDOI

Non-parametric multiple level set model for efficient image classification in urban areas

TL;DR: A closely integrated and effective classification model under variational level set framework has formed and can obtain more accurate and detailed classification than that of relevant methods only depending on spectral information of image.
References
More filters
Journal ArticleDOI

Determination of terrain models in wooded areas with airborne laser scanner data

TL;DR: In this article, the characteristics of laser scanning are compared to photogrammetry with reference to a big pilot project and the results are in accordance with the expectations, however, the geomorphologic quality of the contours, computed from a terrain model derived from laser scanning, needs to be improved.
Journal ArticleDOI

Processing of laser scanner data-algorithms and applications

TL;DR: This paper presents some methods and algorithms concerning filtering for determining the ground surface, DEM, classification of buildings for 3D City Models and the detection of electrical power lines.

Slope based filtering of laser altimetry data

TL;DR: In this article, a new method is proposed for filtering laser data, which is closely related to the erosion operator used for mathematical grey scale morphology, based on height differences in a representative training dataset, filter functions are derived that either preserve important terrain characteristics or minimise the number of classification errors.
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