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StatisticalOutlierRemoval

https://pointclouds.org/documentation/classpcl_1_1_statistical_outlier_removal.html

StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data.

Constructor

new PCL.StatisticalOutlierRemoval(pointType, removed);

Parameters:

NameTypeDefaultDescription
pointTypePointTypePointXYZThe point cloud type.
extractRemovedIndicesbooleanfalseInitializing with true will allow us to extract the removed indices.

Methods

setMeanK

setMeanK(nrK);

Set the number of nearest neighbors to use for mean distance estimation.

Parameters:

NameTypeDefaultDescription
nrKnumberThe number of points to use for mean distance estimation.

getMeanK

getMeanK();

setStddevMulThresh

setStddevMulThresh(stddevMult);

Set the standard deviation multiplier for the distance threshold calculation.

Parameters:

NameTypeDefaultDescription
minPtsnumberThe standard deviation multiplier.

getStddevMulThresh

getStddevMulThresh();

setNegative

See PassThrough.setNegative

getNegative

See PassThrough.getNegative

setKeepOrganized

See PassThrough.setKeepOrganized

getKeepOrganized

See PassThrough.getKeepOrganized

setUserFilterValue

See PassThrough.setUserFilterValue

setInputCloud

See PassThrough.setInputCloud

getInputCloud

See PassThrough.getInputCloud

filter

See PassThrough.filter