40 #ifndef PCL_FILTERS_STATISTICAL_OUTLIER_REMOVAL_H_
41 #define PCL_FILTERS_STATISTICAL_OUTLIER_REMOVAL_H_
43 #include <pcl/filters/filter_indices.h>
44 #include <pcl/search/pcl_search.h>
80 template<
typename Po
intT>
91 typedef boost::shared_ptr< StatisticalOutlierRemoval<PointT> >
Ptr;
92 typedef boost::shared_ptr< const StatisticalOutlierRemoval<PointT> >
ConstPtr;
133 std_mul_ = stddev_mult;
221 std_mul_ (0.0), tree_ (), negative_ (false)
223 filter_name_ =
"StatisticalOutlierRemoval";
267 negative_ = negative;
300 #ifdef PCL_NO_PRECOMPILE
301 #include <pcl/filters/impl/statistical_outlier_removal.hpp>
304 #endif // PCL_FILTERS_STATISTICAL_OUTLIER_REMOVAL_H_
std::string filter_name_
The filter name.
bool getNegative()
Get the value of the internal negative_ parameter.
double getStddevMulThresh()
Get the standard deviation multiplier threshold as set by the user.
int getMeanK()
Get the number of points to use for mean distance estimation.
void applyFilter(PointCloud &output)
Filtered results are stored in a separate point cloud.
void setMeanK(int nr_k)
Set the number of nearest neighbors to use for mean distance estimation.
boost::shared_ptr< pcl::search::Search< PointT > > Ptr
int mean_k_
The number of points to use for mean distance estimation.
void applyFilterIndices(std::vector< int > &indices)
Filtered results are indexed by an indices array.
boost::shared_ptr< const PointCloud< PointT > > ConstPtr
boost::shared_ptr< ::pcl::PCLPointCloud2 const > ConstPtr
boost::shared_ptr< PointCloud< PointT > > Ptr
FilterIndices represents the base class for filters that are about binary point removal.
void setMeanK(int nr_k)
Set the number of points (k) to use for mean distance estimation.
StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data.
bool negative_
If true, the outliers will be returned instead of the inliers (default: false).
void setNegative(bool negative)
Set whether the indices should be returned, or all points except the indices.
pcl::search::Search< PointT >::Ptr SearcherPtr
PointCloud::Ptr PointCloudPtr
boost::shared_ptr< ::pcl::PCLPointCloud2 const > PCLPointCloud2ConstPtr
boost::shared_ptr< ::pcl::PCLPointCloud2 > PCLPointCloud2Ptr
PointCloud::ConstPtr PointCloudConstPtr
StatisticalOutlierRemoval(bool extract_removed_indices=false)
Empty constructor.
KdTreePtr tree_
A pointer to the spatial search object.
int getMeanK()
Get the number of nearest neighbors to use for mean distance estimation.
boost::shared_ptr< ::pcl::PCLPointCloud2 > Ptr
A point structure representing Euclidean xyz coordinates, and the RGB color.
double getStddevMulThresh()
Get the standard deviation multiplier for the distance threshold calculation.
void setStddevMulThresh(double stddev_mult)
Set the standard deviation multiplier for the distance threshold calculation.
boost::shared_ptr< const StatisticalOutlierRemoval< PointT > > ConstPtr
Filter represents the base filter class.
boost::shared_ptr< StatisticalOutlierRemoval< PointT > > Ptr
FilterIndices< PointT >::PointCloud PointCloud
void setStddevMulThresh(double std_mul)
Set the standard deviation multiplier threshold.
StatisticalOutlierRemoval(bool extract_removed_indices=false)
Constructor.
double std_mul_
Standard deviations threshold (i.e., points outside of will be marked as outliers).
void applyFilter(std::vector< int > &indices)
Filtered results are indexed by an indices array.