---
title: "Basic Tutorial | Clean a cloud using automatic filters"
slug: "cyclone-3dr-exercise-clean-a-cloud-using-automatic-filters"
updated: 2026-09-07T11:51:38Z
published: 2026-09-07T11:51:38Z
canonical: "rcdocs.leica-geosystems.com/cyclone-3dr-exercise-clean-a-cloud-using-automatic-filters"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://rcdocs.leica-geosystems.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Basic Tutorial | Clean a cloud using automatic filters

The software provides several automatic filters in order to clean up a point cloud and remove noisy points.

## Automatic Filter: Noise

> [!TIP]
> Open the file **Victory.3dr** ([download](https://www.cyclone3dr.com/download_helper.php?File=Cyclone3DRSampleData/Victory.3dr)).

This file contains 2 point clouds, one with noise, and one already filtered. Show only and select the cloud named “Victory + noise” and go to [Noise](/v1/docs/cyclone-3dr-removenoisec).

If the goal is to delete sparse points inside the cloud, don't check the **Noisy points** option.

The points involved are highlighted and displayed in a different color. You can adjust the slider to remove more or less points. In this example, we can put the **intensity** to 80 in order to remove points which are in fact measurement errors (blue points in the picture).

Information appear in the dialog box to notify you how many points will be deleted.

> [!WARNING]
> Note  
> 
> In order to work correctly, this filter requires a point cloud with a regular density.

![image2019-9-16_14-31-32.png](https://cdn.document360.io/820e11db-8ed5-45ae-ac86-f6b77dcb2aa7/Images/Documentation/image2019-9-16-14-31-32.png)

Remove noisy points in a cloud

## Automatic Segmentation: Distance

> [!TIP]
> Open the file **CleanPointCloud.3dr** ([download](https://www.cyclone3dr.com/download_helper.php?File=Cyclone3DRSampleData/CleanPointCloud.3dr)).

This file contains the point cloud of a dam having noisy and undesired parts.

Select the cloud named “DamRock” and go to [Distance](/v1/docs/cyclone-3dr-explodebydistancec).

Use this filter in order to split the cloud in smaller clouds and isolate the part of the dam. The cloud is split according to the maximum distance between points. This distance also corresponds to the minimum distance between sub clouds. The initial value is computed according to the average density of the cloud. For a first test, you can let it by default and preview the result.

Then, you can change **Segmentation distance** value to fit your needs. Set the parameter to 0.4 m. You can delete automatically the small clouds with the option **Filter small sub-clouds** of less than 10 points. Click on **Preview** to preview the results.

Check the displayed results: Cloud has been exploded into 898 sub-clouds. Then, 789 sub-clouds have been deleted.

Click **OK** to validate the results.

![image2019-9-16_14-33-46.png](https://cdn.document360.io/820e11db-8ed5-45ae-ac86-f6b77dcb2aa7/Images/Documentation/image2019-9-16-14-33-46.png)

Explode a cloud with a distance criterion

All the kept sub clouds are added into the Cloud Group and ordered from biggest to smallest regarding their number of points.

> [!TIP]
> If the cloud is exploded in more than 1000 parts, the smallest will automatically be deleted in order to keep only the 1000 biggest sub clouds.