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/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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 itkHistogramToEntropyImageFilter_h
#define itkHistogramToEntropyImageFilter_h
#include "itkHistogramToImageFilter.h"
namespace itk
{
/**
* \class HistogramToEntropyImageFilter
* \brief The class takes a histogram as an input and gives the entropy
* image as the output. A pixel, at position I, in the output image is given by
*
* \f[
* f(I) = -p \log_2 p
* \f]
*
* where
* \f[
* p = \frac{q_I}{\sum_{i \in I} q_I}
* \f]
* where \f$q_I\f$ is the frequency of measurement vector, I.
*
* \f$p\f$ is the frequency of a measurement vector by the sum of all frequencies =
* Probability of the measurement vector
*
* The output image is of type double.
*
* This is useful in plotting the joint histograms during registration.
*
* \sa HistogramToImageFilter, HistogramToLogProbabilityImageFilter,
* HistogramToIntensityImageFilter, HistogramToProbabilityImageFilter
*
* \ingroup ITKStatistics
*/
namespace Function
{
template <typename TInput, typename TOutput = double>
class HistogramEntropyFunction
{
public:
// Probability function = Number of occurrences in each bin /
// Total Number of occurrences.
//
// Returns pixels of float..
using OutputPixelType = TOutput;
HistogramEntropyFunction() = default;
~HistogramEntropyFunction() = default;
inline OutputPixelType
operator()(const TInput & A) const
{
if (A)
{
const double p = static_cast<OutputPixelType>(A) / static_cast<OutputPixelType>(m_TotalFrequency);
return static_cast<OutputPixelType>((-1) * p * std::log(p) / std::log(2.0));
}
else
{
const double p = static_cast<OutputPixelType>(A + 1) / static_cast<OutputPixelType>(m_TotalFrequency);
return static_cast<OutputPixelType>((-1) * p * std::log(p) / std::log(2.0));
}
}
void
SetTotalFrequency(const SizeValueType n)
{
m_TotalFrequency = n;
}
SizeValueType
GetTotalFrequency() const
{
return m_TotalFrequency;
}
private:
SizeValueType m_TotalFrequency{ 1 };
};
} // namespace Function
template <typename THistogram, typename TImage = Image<double, 3>>
class HistogramToEntropyImageFilter
: public HistogramToImageFilter<THistogram,
TImage,
Function::HistogramEntropyFunction<SizeValueType, typename TImage::PixelType>>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(HistogramToEntropyImageFilter);
/** Standard class type aliases. */
using Self = HistogramToEntropyImageFilter;
/** Standard "Superclass" type alias. */
using Superclass =
HistogramToImageFilter<THistogram,
TImage,
Function::HistogramEntropyFunction<SizeValueType, typename TImage::PixelType>>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(HistogramToEntropyImageFilter);
/** Method for creation through the object factory. */
itkNewMacro(Self);
protected:
HistogramToEntropyImageFilter() = default;
~HistogramToEntropyImageFilter() override = default;
};
} // end namespace itk
#endif
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