00001 /* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Point Cloud Library (PCL) - www.pointclouds.org 00005 * Copyright (c) 2010-2012, Willow Garage, Inc. 00006 * 00007 * All rights reserved. 00008 * 00009 * Redistribution and use in source and binary forms, with or without 00010 * modification, are permitted provided that the following conditions 00011 * are met: 00012 * 00013 * * Redistributions of source code must retain the above copyright 00014 * notice, this list of conditions and the following disclaimer. 00015 * * Redistributions in binary form must reproduce the above 00016 * copyright notice, this list of conditions and the following 00017 * disclaimer in the documentation and/or other materials provided 00018 * with the distribution. 00019 * * Neither the name of Willow Garage, Inc. nor the names of its 00020 * contributors may be used to endorse or promote products derived 00021 * from this software without specific prior written permission. 00022 * 00023 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 00024 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 00025 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 00026 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 00027 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00028 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00029 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00030 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00031 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00032 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00033 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00034 * POSSIBILITY OF SUCH DAMAGE. 00035 * 00036 * $Id: statistical_outlier_removal.h 6144 2012-07-04 22:06:28Z rusu $ 00037 * 00038 */ 00039 00040 #ifndef PCL_FILTERS_STATISTICAL_OUTLIER_REMOVAL_H_ 00041 #define PCL_FILTERS_STATISTICAL_OUTLIER_REMOVAL_H_ 00042 00043 #include <pcl/filters/filter_indices.h> 00044 #include <pcl/search/pcl_search.h> 00045 00046 namespace pcl 00047 { 00080 template<typename PointT> 00081 class StatisticalOutlierRemoval : public FilterIndices<PointT> 00082 { 00083 protected: 00084 typedef typename FilterIndices<PointT>::PointCloud PointCloud; 00085 typedef typename PointCloud::Ptr PointCloudPtr; 00086 typedef typename PointCloud::ConstPtr PointCloudConstPtr; 00087 typedef typename pcl::search::Search<PointT>::Ptr SearcherPtr; 00088 00089 public: 00093 StatisticalOutlierRemoval (bool extract_removed_indices = false) : 00094 FilterIndices<PointT>::FilterIndices (extract_removed_indices), 00095 searcher_ (), 00096 mean_k_ (1), 00097 std_mul_ (0.0) 00098 { 00099 filter_name_ = "StatisticalOutlierRemoval"; 00100 } 00101 00105 inline void 00106 setMeanK (int nr_k) 00107 { 00108 mean_k_ = nr_k; 00109 } 00110 00114 inline int 00115 getMeanK () 00116 { 00117 return (mean_k_); 00118 } 00119 00125 inline void 00126 setStddevMulThresh (double stddev_mult) 00127 { 00128 std_mul_ = stddev_mult; 00129 } 00130 00136 inline double 00137 getStddevMulThresh () 00138 { 00139 return (std_mul_); 00140 } 00141 00142 protected: 00143 using PCLBase<PointT>::input_; 00144 using PCLBase<PointT>::indices_; 00145 using Filter<PointT>::filter_name_; 00146 using Filter<PointT>::getClassName; 00147 using FilterIndices<PointT>::negative_; 00148 using FilterIndices<PointT>::keep_organized_; 00149 using FilterIndices<PointT>::user_filter_value_; 00150 using FilterIndices<PointT>::extract_removed_indices_; 00151 using FilterIndices<PointT>::removed_indices_; 00152 00156 void 00157 applyFilter (PointCloud &output); 00158 00162 void 00163 applyFilter (std::vector<int> &indices) 00164 { 00165 applyFilterIndices (indices); 00166 } 00167 00171 void 00172 applyFilterIndices (std::vector<int> &indices); 00173 00174 private: 00176 SearcherPtr searcher_; 00177 00179 int mean_k_; 00180 00183 double std_mul_; 00184 }; 00185 00196 template<> 00197 class PCL_EXPORTS StatisticalOutlierRemoval<sensor_msgs::PointCloud2> : public Filter<sensor_msgs::PointCloud2> 00198 { 00199 using Filter<sensor_msgs::PointCloud2>::filter_name_; 00200 using Filter<sensor_msgs::PointCloud2>::getClassName; 00201 00202 using Filter<sensor_msgs::PointCloud2>::removed_indices_; 00203 using Filter<sensor_msgs::PointCloud2>::extract_removed_indices_; 00204 00205 typedef pcl::search::Search<pcl::PointXYZ> KdTree; 00206 typedef pcl::search::Search<pcl::PointXYZ>::Ptr KdTreePtr; 00207 00208 typedef sensor_msgs::PointCloud2 PointCloud2; 00209 typedef PointCloud2::Ptr PointCloud2Ptr; 00210 typedef PointCloud2::ConstPtr PointCloud2ConstPtr; 00211 00212 public: 00214 StatisticalOutlierRemoval (bool extract_removed_indices = false) : 00215 Filter<sensor_msgs::PointCloud2>::Filter (extract_removed_indices), mean_k_ (2), 00216 std_mul_ (0.0), tree_ (), negative_ (false) 00217 { 00218 filter_name_ = "StatisticalOutlierRemoval"; 00219 } 00220 00224 inline void 00225 setMeanK (int nr_k) 00226 { 00227 mean_k_ = nr_k; 00228 } 00229 00231 inline int 00232 getMeanK () 00233 { 00234 return (mean_k_); 00235 } 00236 00243 inline void 00244 setStddevMulThresh (double std_mul) 00245 { 00246 std_mul_ = std_mul; 00247 } 00248 00250 inline double 00251 getStddevMulThresh () 00252 { 00253 return (std_mul_); 00254 } 00255 00259 inline void 00260 setNegative (bool negative) 00261 { 00262 negative_ = negative; 00263 } 00264 00269 inline bool 00270 getNegative () 00271 { 00272 return (negative_); 00273 } 00274 00275 protected: 00277 int mean_k_; 00278 00282 double std_mul_; 00283 00285 KdTreePtr tree_; 00286 00288 bool negative_; 00289 00290 void 00291 applyFilter (PointCloud2 &output); 00292 }; 00293 } 00294 00295 #endif // PCL_FILTERS_STATISTICAL_OUTLIER_REMOVAL_H_ 00296