00001 /*========================================================================= 00002 00003 Program: Insight Segmentation & Registration Toolkit 00004 Module: $RCSfile: itkMahalanobisDistanceMembershipFunction.h,v $ 00005 Language: C++ 00006 Date: $Date: 2009-03-04 15:23:56 $ 00007 Version: $Revision: 1.14 $ 00008 00009 Copyright (c) Insight Software Consortium. All rights reserved. 00010 See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details. 00011 00012 This software is distributed WITHOUT ANY WARRANTY; without even 00013 the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR 00014 PURPOSE. See the above copyright notices for more information. 00015 00016 =========================================================================*/ 00017 #ifndef __itkMahalanobisDistanceMembershipFunction_h 00018 #define __itkMahalanobisDistanceMembershipFunction_h 00019 00020 #include <vnl/vnl_vector.h> 00021 #include <vnl/vnl_vector_ref.h> 00022 #include <vnl/vnl_transpose.h> 00023 #include <vnl/vnl_matrix.h> 00024 #include <vnl/algo/vnl_matrix_inverse.h> 00025 #include <vnl/algo/vnl_determinant.h> 00026 #include "itkArray.h" 00027 00028 #include "itkMembershipFunctionBase.h" 00029 00030 00031 namespace itk { 00032 namespace Statistics { 00033 00043 template< class TVector > 00044 class ITK_EXPORT MahalanobisDistanceMembershipFunction : 00045 public MembershipFunctionBase< TVector > 00046 { 00047 public: 00049 typedef MahalanobisDistanceMembershipFunction Self; 00050 typedef MembershipFunctionBase< TVector > Superclass; 00051 typedef SmartPointer<Self> Pointer; 00052 typedef SmartPointer<const Self> ConstPointer; 00053 00055 itkTypeMacro(MahalanobisDistanceMembershipFunction, MembershipFunctionBase); 00056 itkNewMacro(Self); 00058 00060 typedef TVector MeasurementVectorType; 00061 00063 typedef typename Superclass::MeasurementVectorSizeType MeasurementVectorSizeType; 00064 00066 typedef vnl_vector<double> MeanVectorType; 00067 00069 typedef vnl_matrix<double> CovarianceMatrixType; 00070 00072 virtual void SetMeasurementVectorSize( const MeasurementVectorSizeType ); 00073 00075 void SetMean(const MeanVectorType &mean); 00076 void SetMean(const Array< double > &mean); 00078 00080 const MeanVectorType & GetMean() const; 00081 00086 void SetCovariance(const CovarianceMatrixType &cov); 00087 00089 itkGetConstReferenceMacro( Covariance, CovarianceMatrixType ); 00090 00095 void SetInverseCovariance(const CovarianceMatrixType &invcov); 00096 00098 itkGetConstReferenceMacro( InverseCovariance, CovarianceMatrixType ); 00099 00101 itkSetMacro( NumberOfSamples, double ); 00102 00104 itkGetMacro( NumberOfSamples, double ); 00105 00109 double Evaluate(const MeasurementVectorType &measurement) const; 00110 00111 protected: 00112 MahalanobisDistanceMembershipFunction(void); 00113 virtual ~MahalanobisDistanceMembershipFunction(void) {} 00114 void PrintSelf(std::ostream& os, Indent indent) const; 00115 00116 private: 00117 MeanVectorType m_Mean; // mean 00118 CovarianceMatrixType m_Covariance; // covariance matrix 00119 00120 // inverse covariance matrix which is automatically calculated 00121 // when covariace matirx is set. This speed up the GetProbability() 00122 CovarianceMatrixType m_InverseCovariance; 00123 00124 // Number of samples defining this density 00125 double m_NumberOfSamples; 00126 // pre_factor which is automatically calculated 00127 // when covariace matirx is set. This speeds up the GetProbability() 00128 double m_PreFactor; 00129 double m_Epsilon; 00130 double m_DoubleMax; 00131 00132 mutable vnl_matrix< double > m_TempVec; 00133 mutable vnl_matrix< double > m_TempMat; 00134 00135 void CalculateInverseCovariance(); 00136 }; 00137 00138 } // end of namespace Statistics 00139 } // end namespace itk 00140 00141 #ifndef ITK_MANUAL_INSTANTIATION 00142 #include "itkMahalanobisDistanceMembershipFunction.txx" 00143 #endif 00144 00145 #endif 00146