/usr/include/ITK-4.5/itkKullbackLeiblerCompareHistogramImageToImageMetric.h is in libinsighttoolkit4-dev 4.5.0-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 | /*=========================================================================
*
* 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 __itkKullbackLeiblerCompareHistogramImageToImageMetric_h
#define __itkKullbackLeiblerCompareHistogramImageToImageMetric_h
#include "itkCompareHistogramImageToImageMetric.h"
namespace itk
{
/** \class KullbackLeiblerCompareHistogramImageToImageMetric
* \brief Computes the Kubler Lieblach(KL) metric between the histogram
* of the two images to be registered and a training histogram.
*
* This class is templated over the type of the fixed and moving
* images to be compared.
*
* This class computers the KL-metric by comparing the histograms
* of the testing histogram formed by the overlap of intensities in
* the images, to a training histogram. It is based on the
* following paper:
*
* Albert C.S. Chung, William M. Wells III, Alexander Norbash, and
* W. Eric L. Grimson, Multi-modal Image Registration by
* Minimising Kullback-Leibler Distance, In Medical Image Computing
* and Computer-Assisted Intervention - MICCAI 2002, LNCS 2489,
* pp. 525 - 532.
*
* The metric is given by KL(P_test||P_train)
* = Sum_{i1,i2} P_test(i1,i2) vcl_log(P_test(i1,i2)/P_train(i1,i2))
* where P_test and P_train are probabilities given my normalized
* histograms, and i1 and i2 are the intensity bins in the histogram.
*
* \par PARAMETERS
* Epsilon is added to every bin in both histograms. This prevents
* division by zero problems. Epsilon should generally be set to a
* number smaller than one divided by the total number bins in
* the histogram. So, for a 256 by 256 histogram, Epsilon should be
* much less than 1e-5. Tests have shown that choices of epsilon are
* not very important as long as it is small enough. The default is 1e-12.
* I doubt you will need to change it.
*
* \author Samson Timoner
*
* \par SUPPORT
* This work was supported by the Functional Imaging Research in
* Schizophrenia Testbed (FIRST) Biomedical Informatics Research
* Network (BIRN, http://www.birncommunity.org/), which is funded by the
* National Center for Research Resources at the National
* Institutes of Health (NIH). This work is also funded by the
* Neuroimage Analysis Center (P41 RR13218).
*
* \ingroup RegistrationMetrics
* \ingroup ITKRegistrationCommon
*/
template< typename TFixedImage, typename TMovingImage >
class KullbackLeiblerCompareHistogramImageToImageMetric:
public CompareHistogramImageToImageMetric< TFixedImage, TMovingImage >
{
public:
/** Standard class typedefs. */
typedef KullbackLeiblerCompareHistogramImageToImageMetric Self;
typedef CompareHistogramImageToImageMetric< 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(KullbackLeiblerCompareHistogramImageToImageMetric,
HistogramImageToImageMetric);
/** Types transferred from the base class */
typedef typename Superclass::RealType RealType;
typedef typename Superclass::TransformType TransformType;
typedef typename Superclass::TransformPointer TransformPointer;
typedef typename Superclass::ConstPointer TransformConstPointer;
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::FixedImageType FixedImageType;
typedef typename Superclass::MovingImageType MovingImageType;
typedef typename Superclass::FixedImageConstPointer FixedImageConstPointer;
typedef typename Superclass::MovingImageConstPointer
MovingImageConstPointer;
typedef typename Superclass::HistogramType HistogramType;
typedef typename Superclass::HistogramSizeType HistogramSizeType;
typedef typename Superclass::MeasurementVectorType
HistogramMeasurementVectorType;
typedef typename Superclass::HistogramFrequencyType HistogramFrequencyType;
typedef typename Superclass::HistogramIteratorType HistogramIteratorType;
typedef typename Superclass::HistogramPointerType HistogramPointerType;
typedef typename Superclass::InterpolatorType InterpolatorType;
typedef typename Superclass::InterpolatorPointer InterpolatorPointer;
/** Set epsilon, which is added to each bin in both Histogram */
itkSetMacro(Epsilon, double);
/** Get epsilon, the histogram frequency to use if the frequency is 0 */
itkGetConstReferenceMacro(Epsilon, double);
/** Return the number of parameters required by the Transform */
unsigned int GetNumberOfParameters(void) const
{ return this->GetTransform()->GetNumberOfParameters(); }
/** Forms the histogram of the training images to prepare to evaluate the */
/** metric. Must set all parameters first */
void Initialize()
throw ( ExceptionObject );
protected:
/** Constructor is protected to ensure that \c New() function is used to
create instances. */
KullbackLeiblerCompareHistogramImageToImageMetric();
virtual ~KullbackLeiblerCompareHistogramImageToImageMetric(){}
void PrintSelf(std::ostream & os, Indent indent) const;
/** Form the Histogram for the Training data */
void FormTrainingHistogram()
throw ( ExceptionObject );
/** Evaluates the mutual information from the histogram. */
virtual MeasureType EvaluateMeasure(HistogramType & histogram) const;
double m_Epsilon;
private:
// Purposely not implemented.
KullbackLeiblerCompareHistogramImageToImageMetric(Self const &);
void operator=(Self const &); // Purposely not implemented.
};
} // End namespace itk.
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkKullbackLeiblerCompareHistogramImageToImageMetric.hxx"
#endif
#endif // __itkKullbackLeiblerCompareHistogramImageToImageMetric_h
|