Point Cloud Library (PCL)  1.7.0
/tmp/buildd/pcl-1.7-1.7.0/filters/include/pcl/filters/bilateral.h
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00039 
00040 #ifndef PCL_FILTERS_BILATERAL_H_
00041 #define PCL_FILTERS_BILATERAL_H_
00042 
00043 #include <pcl/filters/filter.h>
00044 #include <pcl/search/pcl_search.h>
00045 
00046 namespace pcl
00047 {
00048   /** \brief A bilateral filter implementation for point cloud data. Uses the intensity data channel.
00049     * \note For more information please see 
00050     * <b>C. Tomasi and R. Manduchi. Bilateral Filtering for Gray and Color Images.
00051     * In Proceedings of the IEEE International Conference on Computer Vision,
00052     * 1998.</b>
00053     * \author Luca Penasa
00054     * \ingroup filters
00055     */
00056   template<typename PointT>
00057   class BilateralFilter : public Filter<PointT>
00058   {
00059     using Filter<PointT>::input_;
00060     using Filter<PointT>::indices_;
00061     typedef typename Filter<PointT>::PointCloud PointCloud;
00062     typedef typename pcl::search::Search<PointT>::Ptr KdTreePtr;
00063 
00064     public:
00065 
00066       typedef boost::shared_ptr< BilateralFilter<PointT> > Ptr;
00067       typedef boost::shared_ptr< const BilateralFilter<PointT> > ConstPtr;
00068  
00069 
00070       /** \brief Constructor. 
00071         * Sets sigma_s_ to 0 and sigma_r_ to MAXDBL
00072         */
00073       BilateralFilter () : sigma_s_ (0), 
00074                            sigma_r_ (std::numeric_limits<double>::max ()),
00075                            tree_ ()
00076       {
00077       }
00078 
00079 
00080       /** \brief Filter the input data and store the results into output
00081         * \param[out] output the resultant point cloud message
00082         */
00083       void
00084       applyFilter (PointCloud &output);
00085 
00086       /** \brief Compute the intensity average for a single point
00087         * \param[in] pid the point index to compute the weight for
00088         * \param[in] indices the set of nearest neighor indices 
00089         * \param[in] distances the set of nearest neighbor distances
00090         * \return the intensity average at a given point index
00091         */
00092       double 
00093       computePointWeight (const int pid, const std::vector<int> &indices, const std::vector<float> &distances);
00094 
00095       /** \brief Set the half size of the Gaussian bilateral filter window.
00096         * \param[in] sigma_s the half size of the Gaussian bilateral filter window to use
00097         */
00098       inline void 
00099       setHalfSize (const double sigma_s)
00100       { sigma_s_ = sigma_s; }
00101 
00102       /** \brief Get the half size of the Gaussian bilateral filter window as set by the user. */
00103       inline double
00104       getHalfSize () const
00105       { return (sigma_s_); }
00106 
00107       /** \brief Set the standard deviation parameter
00108         * \param[in] sigma_r the new standard deviation parameter
00109         */
00110       inline void
00111       setStdDev (const double sigma_r)
00112       { sigma_r_ = sigma_r;}
00113 
00114       /** \brief Get the value of the current standard deviation parameter of the bilateral filter. */
00115       inline double
00116       getStdDev () const
00117       { return (sigma_r_); }
00118 
00119       /** \brief Provide a pointer to the search object.
00120         * \param[in] tree a pointer to the spatial search object.
00121         */
00122       inline void
00123       setSearchMethod (const KdTreePtr &tree)
00124       { tree_ = tree; }
00125 
00126     private:
00127 
00128       /** \brief The bilateral filter Gaussian distance kernel.
00129         * \param[in] x the spatial distance (distance or intensity)
00130         * \param[in] sigma standard deviation
00131         */
00132       inline double
00133       kernel (double x, double sigma)
00134       { return (exp (- (x*x)/(2*sigma*sigma))); }
00135 
00136       /** \brief The half size of the Gaussian bilateral filter window (e.g., spatial extents in Euclidean). */
00137       double sigma_s_;
00138       /** \brief The standard deviation of the bilateral filter (e.g., standard deviation in intensity). */
00139       double sigma_r_;
00140 
00141       /** \brief A pointer to the spatial search object. */
00142       KdTreePtr tree_;
00143   };
00144 }
00145 
00146 #ifdef PCL_NO_PRECOMPILE
00147 #include <pcl/filters/impl/bilateral.hpp>
00148 #endif
00149 
00150 #endif // PCL_FILTERS_BILATERAL_H_