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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkNormalizedCorrelationPointSetToImageMetric.h,v $
Language: C++
Date: $Date: 2008-02-03 04:05:29 $
Version: $Revision: 1.23 $
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 __itkNormalizedCorrelationPointSetToImageMetric_h
#define __itkNormalizedCorrelationPointSetToImageMetric_h
#include "itkPointSetToImageMetric.h"
#include "itkCovariantVector.h"
#include "itkPoint.h"
namespace itk
{
/** \class NormalizedCorrelationPointSetToImageMetric
* \brief Computes similarity between pixel values of a point set and
* intensity values of an image.
*
* This metric computes the correlation between point values in the fixed
* point-set and pixel values in the moving image. The correlation is
* normalized by the autocorrelation values of both the point-set and the
* moving image. The spatial correspondence between the point-set and the image
* is established through a Transform. Pixel values are taken from the fixed
* point-set. Their positions are mapped to the moving image and result in
* general in non-grid position on it. Values at these non-grid position of
* the moving image are interpolated using a user-selected Interpolator.
*
* \ingroup RegistrationMetrics
*/
template < class TFixedPointSet, class TMovingImage >
class ITK_EXPORT NormalizedCorrelationPointSetToImageMetric :
public PointSetToImageMetric< TFixedPointSet, TMovingImage>
{
public:
/** Standard class typedefs. */
typedef NormalizedCorrelationPointSetToImageMetric Self;
typedef PointSetToImageMetric<TFixedPointSet, TMovingImage > Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Run-time type information (and related methods). */
itkTypeMacro(NormalizedCorrelationPointSetToImageMetric,
PointSetToImageMetric);
/** Types transferred from the base class */
typedef typename Superclass::RealType RealType;
typedef typename Superclass::TransformType TransformType;
typedef typename Superclass::TransformPointer TransformPointer;
typedef typename Superclass::TransformParametersType TransformParametersType;
typedef typename Superclass::TransformJacobianType TransformJacobianType;
typedef typename Superclass::GradientPixelType GradientPixelType;
typedef typename Superclass::MeasureType MeasureType;
typedef typename Superclass::DerivativeType DerivativeType;
typedef typename Superclass::FixedPointSetType FixedPointSetType;
typedef typename Superclass::MovingImageType MovingImageType;
typedef typename Superclass::FixedPointSetConstPointer FixedPointSetConstPointer;
typedef typename Superclass::MovingImageConstPointer MovingImageConstPointer;
typedef typename Superclass::PointIterator PointIterator;
typedef typename Superclass::PointDataIterator PointDataIterator;
typedef typename Superclass::InputPointType InputPointType;
typedef typename Superclass::OutputPointType OutputPointType;
/** Get the derivatives of the match measure. */
void GetDerivative( const TransformParametersType & parameters,
DerivativeType & Derivative ) const;
/** Get the value for single valued optimizers. */
MeasureType GetValue( const TransformParametersType & parameters ) const;
/** Get value and derivatives for multiple valued optimizers. */
void GetValueAndDerivative( const TransformParametersType & parameters,
MeasureType& Value, DerivativeType& Derivative ) const;
/** Set/Get SubtractMean boolean. If true, the sample mean is subtracted
* from the sample values in the cross-correlation formula and
* typically results in narrower valleys in the cost fucntion.
* Default value is false. */
itkSetMacro( SubtractMean, bool );
itkGetConstReferenceMacro( SubtractMean, bool );
itkBooleanMacro( SubtractMean );
protected:
NormalizedCorrelationPointSetToImageMetric();
virtual ~NormalizedCorrelationPointSetToImageMetric() {};
void PrintSelf(std::ostream& os, Indent indent) const;
private:
NormalizedCorrelationPointSetToImageMetric(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
bool m_SubtractMean;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkNormalizedCorrelationPointSetToImageMetric.txx"
#endif
#endif
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