CSF (Cloth Simulation Filter)
Separating point clouds into ground and non-ground measurements is an essential step to generate digital terrain models (DTMs) from LiDAR (light detection and ranging) data. Many filtering algorithms have been developed. However, even state-of-the-art filtering algorithms need to set up a number of complicated parameters carefully to achieve high accuracy.
For the purpose of reducing the parameters users to set, and promoting the filtering algorithms, we present a new filtering method which only needs a few easy-to-set integer and Boolean parameters. This method is based on cloth simulation which is a 3D computer graphics algorithm and is used for simulating cloth within a computer program. So our filtering algorithm is called cloth simulation filtering, CSF.
More information of CSF and its parameters can be found at http://www.cloudcompare.org/doc/wiki/index.php?title=CSF_(plugin).
CSF implemented the algorithm proposed by the paper "Zhang W, Qi J, Wan P, Wang H, Xie D, Wang X, Yan G. An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sensing. 2016; 8(6):501.",which can be downloaded from https://www.researchgate.net/profile/Wuming_Zhang2. Please cite this paper, if you use this software in your work.
The usage is very simple. [groundIndex,nonGroundIndex] = csf_filtering(pointcloud,typeofscene,postprocessing,gridsize); Sometime, only the type of the scene is needed to be set by the user. More details can be found in demos.
CSF has been integrated into two free softwares for point cloud processing. If you want to use it with a graphical user interface (GUI), you can download CloudCompare from http://www.cloudcompare.org/ or Point Cloud Magic from http://lidar.radi.ac.cn (In Chinese).
Cite As
wpqjbzwm wpqjbzwm (2023). CSF (Cloth Simulation Filter) (https://github.com/jianboqi/CSF), GitHub. Retrieved .
Zhang W, Qi J, Wan P, Wang H, Xie D, Wang X, Yan G. An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sensing. 2016; 8(6):501.
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- Mathematics and Optimization > Mapping Toolbox > Data Analysis >
- Radar > Mapping Toolbox > Data Analysis >
- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Classification >
- Robotics and Autonomous Systems > Automated Driving Toolbox > Detection and Tracking > Lidar Processing >
- Automotive > Automated Driving Toolbox > Detection and Tracking > Lidar Processing >
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Versions that use the GitHub default branch cannot be downloaded
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1.2.2.2 | Minor changes to title and summary. |
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1.2.2.0 | Fix some small bugs when using CSF with Matlab |
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1.2.1.0 | we get a lot of feedbacks from different users around the world, the new version has been enhanced by:
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1.2.0.0 | We get a lot of feedbacks from different users around the world, the new version has been enhanced by:
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1.1.0.0 | Three more options are added to input parameters.
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1.0.0.0 |