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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkNormalizedCorrelationImageToImageMetric_h
#define itkNormalizedCorrelationImageToImageMetric_h
#include "itkImageToImageMetric.h"
#include "itkPoint.h"
namespace itk
{
/** \class NormalizedCorrelationImageToImageMetric
* \brief Computes similarity between two images to be registered
*
* This metric computes the correlation between pixels in the fixed image
* and pixels in the moving image. The spatial correspondance between
* fixed and moving image is established through a Transform. Pixel values are
* taken from the fixed image, 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. The correlation is normalized by the autocorrelations of both
* the fixed and moving images.
*
* A more negative metric value indicates a greater degree of correlation
* between the fixed and moving image. This makes the metric simpler to use
* with optimizers that strive to minimize their cost function by default.
*
* \ingroup RegistrationMetrics
* \ingroup ITKRegistrationCommon
*/
template< typename TFixedImage, typename TMovingImage >
class ITK_TEMPLATE_EXPORT NormalizedCorrelationImageToImageMetric:
public ImageToImageMetric< TFixedImage, TMovingImage >
{
public:
/** Standard class typedefs. */
typedef NormalizedCorrelationImageToImageMetric Self;
typedef ImageToImageMetric< TFixedImage, 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(NormalizedCorrelationImageToImageMetric, Object);
/** 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::OutputPointType OutputPointType;
typedef typename Superclass::InputPointType InputPointType;
typedef typename Superclass::MeasureType MeasureType;
typedef typename Superclass::DerivativeType DerivativeType;
typedef typename Superclass::FixedImageType FixedImageType;
typedef typename Superclass::MovingImageType MovingImageType;
typedef typename Superclass::FixedImageConstPointer FixedImageConstPointer;
typedef typename Superclass::MovingImageConstPointer MovingImageConstPointer;
/** Get the derivatives of the match measure. */
void GetDerivative(const TransformParametersType & parameters,
DerivativeType & Derivative) const ITK_OVERRIDE;
/** Get the value for single valued optimizers. */
MeasureType GetValue(const TransformParametersType & parameters) const ITK_OVERRIDE;
/** Get value and derivatives for multiple valued optimizers. */
void GetValueAndDerivative(const TransformParametersType & parameters,
MeasureType & Value, DerivativeType & Derivative) const ITK_OVERRIDE;
/** 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 function.
* Default value is false. */
itkSetMacro(SubtractMean, bool);
itkGetConstReferenceMacro(SubtractMean, bool);
itkBooleanMacro(SubtractMean);
protected:
NormalizedCorrelationImageToImageMetric();
virtual ~NormalizedCorrelationImageToImageMetric() ITK_OVERRIDE {}
void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
private:
ITK_DISALLOW_COPY_AND_ASSIGN(NormalizedCorrelationImageToImageMetric);
bool m_SubtractMean;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkNormalizedCorrelationImageToImageMetric.hxx"
#endif
#endif
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