/usr/include/OTB-6.4/otbMRFSamplerRandom.h is in libotb-dev 6.4.0+dfsg-1.
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* Copyright (C) 2005-2017 Centre National d'Etudes Spatiales (CNES)
*
* This file is part of Orfeo Toolbox
*
* https://www.orfeo-toolbox.org/
*
* 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
*
* 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 otbMRFSamplerRandom_h
#define otbMRFSamplerRandom_h
#include "otbMRFSampler.h"
#include "itkMersenneTwisterRandomVariateGenerator.h"
#include "itkNumericTraits.h"
namespace otb
{
/**
* \class MRFSamplerRandom
* \brief This is the base class for sampler methods used in the MRF framework.
*
* This is one sampler to be used int he MRF framework. This sampler select the
* value randomly according to a uniform probability.
*
*
* This class is meant to be used in the MRF framework with the otb::MarkovRandomFieldFilter
*
* \ingroup Markov
*
* \ingroup OTBMarkov
*/
template<class TInput1, class TInput2>
class ITK_EXPORT MRFSamplerRandom : public MRFSampler<TInput1, TInput2>
{
public:
typedef MRFSamplerRandom Self;
typedef otb::MRFSampler<TInput1, TInput2> Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
typedef typename Superclass::InputImageNeighborhoodIterator InputImageNeighborhoodIterator;
typedef typename Superclass::LabelledImageNeighborhoodIterator LabelledImageNeighborhoodIterator;
typedef typename Superclass::LabelledImagePixelType LabelledImagePixelType;
typedef typename Superclass::InputImagePixelType InputImagePixelType;
typedef typename Superclass::EnergyFidelityType EnergyFidelityType;
typedef typename Superclass::EnergyRegularizationType EnergyRegularizationType;
typedef typename Superclass::EnergyFidelityPointer EnergyFidelityPointer;
typedef typename Superclass::EnergyRegularizationPointer EnergyRegularizationPointer;
typedef itk::Statistics::MersenneTwisterRandomVariateGenerator RandomGeneratorType;
itkNewMacro(Self);
itkTypeMacro(MRFSamplerRandom, MRFSampler);
inline int Compute(const InputImageNeighborhoodIterator& itData, const LabelledImageNeighborhoodIterator& itRegul) ITK_OVERRIDE
{
this->m_EnergyBefore = this->m_EnergyFidelity->GetValue(itData, itRegul.GetCenterPixel());
this->m_EnergyBefore += this->m_Lambda
* this->m_EnergyRegularization->GetValue(itRegul, itRegul.GetCenterPixel());
this->m_Value = static_cast<LabelledImagePixelType>(m_Generator->GetIntegerVariate() % this->m_NumberOfClasses);
this->m_EnergyAfter = this->m_EnergyFidelity->GetValue(itData, this->m_Value);
this->m_EnergyAfter += this->m_Lambda * this->m_EnergyRegularization->GetValue(itRegul, this->m_Value);
this->m_DeltaEnergy = this->m_EnergyAfter - this->m_EnergyBefore;
return 0;
}
/** Methods to cancel random effects.*/
void InitializeSeed(int seed)
{
m_Generator->SetSeed(seed);
}
void InitializeSeed()
{
m_Generator->SetSeed();
}
protected:
// The constructor and destructor.
MRFSamplerRandom()
{
m_Generator = RandomGeneratorType::GetInstance();
m_Generator->SetSeed();
}
~MRFSamplerRandom() ITK_OVERRIDE {}
private:
RandomGeneratorType::Pointer m_Generator;
};
}
#endif
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