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AddingNoise.cpp
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AddingNoise.cpp
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/*
* AddingNoise.cpp
*
* Created on: May 22, 2015
* Author: dbazazian
*/
// #define STANDARD_DEVIATION_NEIGHBORS
#define GAUSSIAN_NOISE
#ifdef STANDARD_DEVIATION_NEIGHBORS
#include <iostream>
#include <stdio.h> /* printf, NULL */
#include <stdlib.h> /* srand, rand */
#include "time.h"
#include <boost/thread/thread.hpp>
#include <pcl/common/common_headers.h>
#include <pcl/features/normal_3d.h>
#include <pcl/io/io.h>
#include <pcl/io/pcd_io.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <pcl/visualization/cloud_viewer.h>
#include <pcl/console/parse.h>
#include <pcl/io/ply_io.h>
int
main (int argc, char*argv[])
{
pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZRGBA>);
pcl::PointCloud<pcl::PointXYZRGBA>::Ptr Noisycloud (new pcl::PointCloud<pcl::PointXYZRGBA>);
// pcl::io::loadPCDFile ("path/to/OnePlane.pcd", *cloud);
// pcl::io::loadPCDFile ("path/to/CubeSharpEdge.pcd", *cloud);
pcl::io::loadPCDFile ("path/to/CubeFractal2.pcd", *cloud);
std::cout << "Number of points in the input cloud is:"<< cloud->points.size() << std::endl;
Noisycloud->resize(cloud ->points.size () );
// creat kdtree
pcl::KdTreeFLANN<pcl::PointXYZRGBA> kdtree;
kdtree.setInputCloud (cloud);
pcl::PointXYZRGBA searchPoint;
// K nearest neighbor search
int NumbersNeighbor = 12; // numbers of neighbors 7
std::vector<int> NeighborsKNSearch(NumbersNeighbor);
std::vector<float> NeighborsKNSquaredDistance(NumbersNeighbor);
double* StndDevX = new double [cloud->points.size() ];
double* StndDevY = new double [cloud->points.size() ];
double* StndDevZ = new double [cloud->points.size() ];
//All the Points of the cloud
for (size_t i = 0; i < cloud ->points.size (); ++i) {
searchPoint.x = cloud->points[i].x;
searchPoint.y = cloud->points[i].y;
searchPoint.z = cloud->points[i].z;
if ( kdtree.nearestKSearch (searchPoint, NumbersNeighbor, NeighborsKNSearch, NeighborsKNSquaredDistance) > 0 ) {
NumbersNeighbor = NeighborsKNSearch.size (); }
else { NumbersNeighbor = 0; }
// computing VAriance
double sumX = 0.00 ; double sumY = 0.00 ; double sumZ = 0.00 ;
for (size_t ii = 0; ii < NeighborsKNSearch.size (); ++ii) {
sumX += (cloud->points[ NeighborsKNSearch[ii] ].x);
sumY += (cloud->points[ NeighborsKNSearch[ii] ].y);
sumZ += (cloud->points[ NeighborsKNSearch[ii] ].z);
} // For each neighbor of the query point
double AvgX = sumX / NeighborsKNSearch.size () ; double AvgY = sumY / NeighborsKNSearch.size () ; double AvgZ= sumZ / NeighborsKNSearch.size () ;
sumX = 0.00 ; sumY = 0.00 ; sumZ = 0.00 ;
for (size_t ii = 0; ii < NeighborsKNSearch.size (); ++ii) {
sumX += ( ((cloud->points[ NeighborsKNSearch[ii] ].x) - AvgX) * ((cloud->points[ NeighborsKNSearch[ii] ].x) - AvgX) ) ;
sumY += ( ((cloud->points[ NeighborsKNSearch[ii] ].y) - AvgY) * ((cloud->points[ NeighborsKNSearch[ii] ].y) - AvgY) ) ;
sumZ += ( ((cloud->points[ NeighborsKNSearch[ii] ].z) - AvgZ) * ((cloud->points[ NeighborsKNSearch[ii] ].z) - AvgZ) ) ;
} // For each neighbor of the query point
StndDevX [i] = sqrt(sumX / ( NeighborsKNSearch.size () - 1)) ;
StndDevY [i] = sqrt(sumY / ( NeighborsKNSearch.size () - 1)) ;
StndDevZ [i] = sqrt(sumZ / ( NeighborsKNSearch.size () - 1)) ;
} // For each Point of the Cloud
// First copy all the points of main cloud to the noisy cloud
for (size_t i = 0; i < Noisycloud ->points.size (); ++i ) {
// Noisy point cloud
Noisycloud->points[i].x = cloud->points[i].x;
Noisycloud->points[i].y = cloud->points[i].y;
Noisycloud->points[i].z = cloud->points[i].z;
Noisycloud->points[i].r = 255;
Noisycloud->points[i].g = 255;
Noisycloud->points[i].b = 255;
}
// Then add noise to each 10 point of the cloud
for (size_t i = 0; i < Noisycloud ->points.size (); i+=10 ) {
// Noisy point cloud
Noisycloud->points[i].x = cloud->points[i].x + (7* StndDevX[i]);
Noisycloud->points[i].y = cloud->points[i].y + (7* StndDevY[i]);
Noisycloud->points[i].z = cloud->points[i].z + (7* StndDevZ[i]);
Noisycloud->points[i].r = 255;
Noisycloud->points[i].g = 255;
Noisycloud->points[i].b = 255;
}
std::cout << "Number of points in the Noisy cloud is:"<< Noisycloud->points.size() << std::endl;
// write red point cloud to disk
pcl::io::savePCDFile ("path/to//AddingNoise/Frac2withNoise710.pcd", *Noisycloud);
pcl::PLYWriter writePLY;
writePLY.write ("path/to//AddingNoise/Frac2withNoise710.ply", *Noisycloud, false);
// Show the cloud
//pcl::visualization::CloudViewer viewer(" ONePlaneWithNoise ");
//viewer.showCloud(Noisycloud);
//while (!viewer.wasStopped ())
//{}
return (0);
}
#endif
#ifdef GAUSSIAN_NOISE
#include <iostream>
#include <stdio.h> /* printf, NULL */
#include <stdlib.h> /* srand, rand */
#include <math.h>
#include "time.h"
#include <boost/thread/thread.hpp>
#include <pcl/common/common_headers.h>
#include <pcl/features/normal_3d.h>
#include <pcl/io/io.h>
#include <pcl/io/pcd_io.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <pcl/visualization/cloud_viewer.h>
#include <pcl/console/parse.h>
#include <pcl/io/ply_io.h>
#define PI 3.14159265
int
main (int argc, char*argv[])
{
pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZRGBA>);
pcl::PointCloud<pcl::PointXYZRGBA>::Ptr Noisycloud (new pcl::PointCloud<pcl::PointXYZRGBA>);
// pcl::io::loadPCDFile ("path/to/OnePlane.pcd", *cloud);
// pcl::io::loadPCDFile ("path/to/CubeSharpEdge.pcd", *cloud);
// pcl::io::loadPCDFile ("path/to/CubeFractal2.pcd", *cloud);
// pcl::io::loadPCDFile ("path/to/TwoPlane22.pcd", *cloud);
// pcl::io::loadPCDFile ("path/to/bunny.pcd",*cloud);
pcl::io::loadPCDFile ("path/to/Tetrahedron.pcd", *cloud);
std::cout << "Number of points in the input cloud is:"<< cloud->points.size() << std::endl;
Noisycloud->resize(cloud ->points.size () );
// First copy all the points of main cloud to the noisy cloud
for (size_t i = 0; i < Noisycloud ->points.size (); ++i ) {
// Noisy point cloud
Noisycloud->points[i].x = cloud->points[i].x;
Noisycloud->points[i].y = cloud->points[i].y;
Noisycloud->points[i].z = cloud->points[i].z;
Noisycloud->points[i].r = 255;
Noisycloud->points[i].g = 255;
Noisycloud->points[i].b = 255;
}
double* GussNosX = new double [cloud->points.size() ];
double* GussNosY = new double [cloud->points.size() ];
double* GussNosZ = new double [cloud->points.size() ];
double variance = 0.3 ;
double mean = 0.00;
// http://forums.codeguru.com/showthread.php?459963-Adding-noise-to-image
//All the Points of the cloud
for (size_t i = 0; i < cloud ->points.size (); i+=35) { // 10 , 50
double u1 = (((((float) rand()) / (float) RAND_MAX) * (0.003 - 0.00)) + 0.00) ;
double u2 = (((((float) rand()) / (float) RAND_MAX) * (0.003- 0.00)) + 0.00) ;
// if (u1 > 0.005 ) u1 = 0.005;
// temp = sqrt(-2.0*variance*log(u1));
// tempint = p[ix][iy] + (int) (temp * sin(TWO_PI*u2) + mean);
double temp = sqrt(-2.0*variance*log(u1));
double tempin = (temp * sin(2* PI *u2) + mean);
Noisycloud->points[i].x = cloud->points[i].x + tempin;
Noisycloud->points[i].y = cloud->points[i].y + tempin;
Noisycloud->points[i].z = cloud->points[i].z + tempin;
}// For each point
// Then add noise to each 10 point of the cloud
// for (size_t i = 0; i < Noisycloud ->points.size (); i+=10 ) {
// // Noisy point cloud
// Noisycloud->points[i].x = cloud->points[i].x + (7* StndDevX[i]);
// Noisycloud->points[i].y = cloud->points[i].y + (7* StndDevY[i]);
// Noisycloud->points[i].z = cloud->points[i].z + (7* StndDevZ[i]);
// Noisycloud->points[i].r = 255;
// Noisycloud->points[i].g = 255;
// Noisycloud->points[i].b = 255;
// }
std::cout << "Number of points in the Noisy cloud is:"<< Noisycloud->points.size() << std::endl;
// write red point cloud to disk
// pcl::io::savePCDFile ("path/to/AddingNoise/Two22plane14Noise.pcd", *Noisycloud);
// pcl::io::savePCDFile ("path/to/AddingNoise/Bunny03Noise50.pcd", *Noisycloud);
pcl::io::savePCDFile ("path/to/AddingNoise/TetrahedronNoise35.pcd", *Noisycloud);
// pcl::io::savePCDFile ("path/to/AddingNoise/Frac2Guass14Noise.pcd", *Noisycloud);
// pcl::io::savePCDFile ("path/to/AddingNoise/Frac2withNoise710.pcd", *Noisycloud);
pcl::PLYWriter writePLY;
writePLY.write ("path/to//AddingNoise/TetrahedronNoise35.ply", *Noisycloud, false);
// writePLY.write ("path/to//AddingNoise/Bunny03Noise50.ply", *Noisycloud, false);
// writePLY.write ("path/to/AddingNoise/Frac2Guass14Noise.ply", *Noisycloud, false);
// writePLY.write ("path/to/AddingNoise/Frac2withNoise710.ply", *Noisycloud, false);
// Show the cloud
pcl::visualization::CloudViewer viewer(" ONePlaneWithNoise ");
viewer.showCloud(Noisycloud);
while (!viewer.wasStopped ())
{}
return (0);
}
#endif