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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkKullbackLeiblerCompareHistogramImageToImageMetric.txx,v $
Language: C++
Date: $Date: 2006-03-19 04:36:54 $
Version: $Revision: 1.4 $
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 __itkKullbackLeiblerCompareHistogramImageToImageMetric_txx
#define __itkKullbackLeiblerCompareHistogramImageToImageMetric_txx
#include "itkKullbackLeiblerCompareHistogramImageToImageMetric.h"
#include "itkHistogram.h"
// Todo: need to access Use_Padding in parent. Make in protected
// need to figure out what to do when "stuff" is not in histogram
// kernel function?
namespace itk
{
template <class TFixedImage, class TMovingImage>
KullbackLeiblerCompareHistogramImageToImageMetric<TFixedImage, TMovingImage>::
KullbackLeiblerCompareHistogramImageToImageMetric()
{
m_Epsilon = 1e-12; // should be smaller than 1/numBins^2
}
template <class TFixedImage, class TMovingImage>
void
KullbackLeiblerCompareHistogramImageToImageMetric<TFixedImage, TMovingImage>
::Initialize() throw (ExceptionObject)
{
Superclass::Initialize();
}
template <class TFixedImage, class TMovingImage>
typename KullbackLeiblerCompareHistogramImageToImageMetric<TFixedImage, \
TMovingImage>::MeasureType
KullbackLeiblerCompareHistogramImageToImageMetric<TFixedImage, \
TMovingImage>
::EvaluateMeasure(HistogramType& histogram) const
{
// Two terms.
// First the term that measures the entropy of the term
// p(x,y) log p(x,y) - p(x,y) log q(x,y)
MeasureType KullbackLeibler = NumericTraits<MeasureType>::Zero;
HistogramIteratorType measured_it = histogram.Begin();
HistogramIteratorType measured_end = histogram.End();
HistogramIteratorType training_it = this->GetTrainingHistogram()->Begin();
HistogramIteratorType training_end = this->GetTrainingHistogram()->End();
while (measured_it != measured_end)
{
// Every bin gets epsilon added to it
double TrainingFreq = training_it.GetFrequency()+m_Epsilon;
double MeasuredFreq = measured_it.GetFrequency()+m_Epsilon;
KullbackLeibler += MeasuredFreq*vcl_log(MeasuredFreq/TrainingFreq);
++measured_it;
++training_it;
}
if (training_it != training_end)
itkWarningMacro("The Measured and Training Histograms have different number of bins.");
// Get the total frequency for each histogram.
HistogramFrequencyType totalTrainingFreq = this->GetTrainingHistogram()->GetTotalFrequency();
HistogramFrequencyType totalMeasuredFreq = histogram.GetTotalFrequency();
// The actual number of total frequency is a bit larger
// than the number of counts because we add m_Epsilon to every bin
double AdjustedTotalTrainingFreq = totalTrainingFreq +
this->GetHistogramSize()[0]*this->GetHistogramSize()[1]*m_Epsilon;
double AdjustedTotalMeasuredFreq = totalMeasuredFreq +
this->GetHistogramSize()[0]*this->GetHistogramSize()[1]*m_Epsilon;
KullbackLeibler = KullbackLeibler/static_cast<MeasureType>(AdjustedTotalMeasuredFreq)
- vcl_log(AdjustedTotalMeasuredFreq/AdjustedTotalTrainingFreq);
return KullbackLeibler;
}
template <class TFixedImage, class TMovingImage>
void KullbackLeiblerCompareHistogramImageToImageMetric<TFixedImage, TMovingImage>::
PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "Epsilon: " << m_Epsilon << std::endl;
}
} // End namespace itk
#endif // itkKullbackLeiblerCompareHistogramImageToImageMetric_txx
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