itkMahalanobisDistanceMetric.h

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/*=========================================================================

  Program:   Insight Segmentation & Registration Toolkit
  Module:    $RCSfile: itkMahalanobisDistanceMetric.h,v $
  Language:  C++
  Date:      $Date: 2009-05-02 05:43:56 $
  Version:   $Revision: 1.1 $

  Copyright (c) Insight Software Consortium. All rights reserved.
  See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.

     This software is distributed WITHOUT ANY WARRANTY; without even
     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
     PURPOSE.  See the above copyright notices for more information.

=========================================================================*/
#ifndef __itkMahalanobisDistanceMetric_h
#define __itkMahalanobisDistanceMetric_h

#include <vnl/vnl_vector.h>
#include <vnl/vnl_vector_ref.h>
#include <vnl/vnl_transpose.h>
#include <vnl/vnl_matrix.h>
#include <vnl/algo/vnl_matrix_inverse.h>
#include <vnl/algo/vnl_determinant.h>
#include "itkArray.h"

#include "itkDistanceMetric.h"


namespace itk {
namespace Statistics{

template< class TVector >
class ITK_EXPORT MahalanobisDistanceMetric :
    public DistanceMetric< TVector >
{
public:
  typedef MahalanobisDistanceMetric                 Self;
  typedef DistanceMetric< TVector >                 Superclass;
  typedef SmartPointer<Self>                        Pointer;
  typedef SmartPointer<const Self>                  ConstPointer;

  itkTypeMacro(MahalanobisDistanceMetric, DistanceMetric);
  itkNewMacro(Self);


  typedef typename Superclass::MeasurementVectorType  MeasurementVectorType;

  typedef typename Superclass::MeasurementVectorSizeType MeasurementVectorSizeType;


  typedef typename Superclass::OriginType MeanVectorType;

  typedef vnl_matrix<double>  CovarianceMatrixType;

  virtual void SetMeasurementVectorSize( MeasurementVectorSizeType );

  void SetMean(const MeanVectorType &mean);

  const MeanVectorType & GetMean() const;

  void SetCovariance(const CovarianceMatrixType &cov);

  itkGetConstReferenceMacro( Covariance, CovarianceMatrixType );

  void SetInverseCovariance(const CovarianceMatrixType &invcov);

  itkGetConstReferenceMacro( InverseCovariance, CovarianceMatrixType );

  double Evaluate(const MeasurementVectorType &measurement) const;

  double Evaluate(const MeasurementVectorType &x1, const MeasurementVectorType &x2) const; 

  itkSetMacro( Epsilon, double );
  itkGetConstMacro( Epsilon, double );

  itkSetMacro( DoubleMax, double );
  itkGetConstMacro( DoubleMax, double );

protected:
  MahalanobisDistanceMetric(void);
  virtual ~MahalanobisDistanceMetric(void) {}
  void PrintSelf(std::ostream& os, Indent indent) const;

private:
  MeanVectorType        m_Mean;              // mean
  CovarianceMatrixType  m_Covariance;        // covariance matrix

  // inverse covariance matrix which is automatically calculated
  // when covariace matirx is set.  This speed up the GetProbability()
  CovarianceMatrixType  m_InverseCovariance;

  double       m_Epsilon;
  double       m_DoubleMax;
 
  void CalculateInverseCovariance();

};

} // end of namespace Statistics
} // end namespace itk

#ifndef ITK_MANUAL_INSTANTIATION
#include "itkMahalanobisDistanceMetric.txx"
#endif

#endif

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