lidR: smooth_height – R documentation

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smooth_height

Smooth a point cloud

Description

Point cloud-based smoothing algorithm. Two methods are available: average within a window and Gaussian smooth within a window. The attribute Z of the returned LAS object is the smoothed Z. A new attribute Zraw is added to store the original values and can be used to restore the point cloud with unsmooth_height.

Usage

smooth_height(
  las,
  size,
  method = c("average", "gaussian"),
  shape = c("circle", "square"),
  sigma = size/6
)

unsmooth_height(las)

Arguments

`las`	An object of class `LAS`
`size`	numeric. The size of the windows used to smooth.
`method`	character. Smoothing method. Can be 'average' or 'gaussian'.
`shape`	character. The shape of the windows. Can be circle or square.
`sigma`	numeric. The standard deviation of the gaussian if the method is gaussian.

Details

This method does not use raster-based methods to smooth the point cloud. This is a true point cloud smoothing. It is not really useful by itself but may be interesting in combination with filters such as filter_surfacepoints, for example to develop new algorithms.

Value

An object of the class LAS.

Examples

LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")
las <- readLAS(LASfile, select = "xyz")

las <- filter_surfacepoints(las, 1)
#plot(las)

las <- smooth_height(las, 5, "gaussian", "circle", sigma = 2)
#plot(las)

las <- unsmooth_height(las)
#plot(las)

lidR

Airborne LiDAR Data Manipulation and Visualization for Forestry Applications

v3.1.2

GPL-3

Authors

Jean-Romain Roussel [aut, cre, cph], David Auty [aut, ctb] (Reviews the documentation), Florian De Boissieu [ctb] (Fixed bugs and improved catalog features), Andrew Sánchez Meador [ctb] (Implemented wing2015() for segment_snags()), Bourdon Jean-François [ctb] (Contributed to Roussel2020() for track_sensor()), Gatziolis Demetrios [ctb] (Implemented Gatziolis2019() for track_sensor())

Initial release

2021-03-11