# CloudClean
**CloudClean** is used to make a smart-decimated cloud, or to increase the precision on surfaces. Smart decimation refers to reducing the density of a pointcloud by removing points furthest from estimated surfaces in the cloud.
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Users have several options for improving precision on hard surfaces. CloudClean decimated will attempt to improve precision without reducing density, similar to [Statistical Outlier Removal](/spatialexplorer-8-and-9/user-interface/toolbars/analytics/classify/classify-statistical-outliers.md) (SOR). The primary difference between the two tools is that SOR will result in a changed classification (assigning points to noise class), whereas CloudClean will create an entirely new pointcloud. For a more arbitrary form of decimation, configure the[ lidar processing settings](/spatialexplorer-8-and-9/user-interface/windows/project/rover/lidars/lidar-processing-settings.md) to exclude every other line, or as is the case with multi-laser systems, utilize auto-downsampling.
{% endhint %}
**Output Mode:** Choose between created *Decimated*, *Projected*, or both clouds
**Points per Square Meter:** Target point density for the output cloud. Used only with *Decimated* mode.
**Uniformity:** A value of 1 will try to maximize uniform density in the pointcloud. A value of 0 will disregard uniformity and focus only on improving surface precision. Most users will want to use the default value of 0.
### Output Mode:
**Decimated:** Given point density, algorithm picks points that are nearest to the computed surface. It then keeps original points from the cloud, but discards the points furthest away from computed surface.
**Projected:** Projects every original point to a computed surface. It keeps all the points from the cloud, but moves or 'projects' them closer to the computed surface.
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