From 2f1159ecc27f0f4e05054124ba003bf543a2e07b Mon Sep 17 00:00:00 2001
From: Emmanuel Christophe <emmanuel.christophe@orfeo-toolbox.org>
Date: Sat, 8 Aug 2009 10:49:46 +0800
Subject: [PATCH] REFAC: cleaning Markov
---
Code/Markov/otbMRFEnergy.h | 17 ++++---
Code/Markov/otbMRFEnergyEdgeFidelity.h | 1 -
Code/Markov/otbMRFEnergyGaussian.h | 2 -
.../otbMRFEnergyGaussianClassification.h | 2 -
Code/Markov/otbMRFOptimizer.h | 8 ++--
Code/Markov/otbMRFSampler.h | 16 +++----
Code/Markov/otbMRFSamplerRandomMAP.h | 48 +++++++++----------
Code/Markov/otbMarkovRandomFieldFilter.h | 1 -
Code/Markov/otbMarkovRandomFieldFilter.txx | 23 ++-------
9 files changed, 49 insertions(+), 69 deletions(-)
diff --git a/Code/Markov/otbMRFEnergy.h b/Code/Markov/otbMRFEnergy.h
index 9c98ac1c0d..3aafb37c99 100644
--- a/Code/Markov/otbMRFEnergy.h
+++ b/Code/Markov/otbMRFEnergy.h
@@ -133,10 +133,10 @@ public:
protected:
// The constructor and destructor.
- MRFEnergy()
- {
- m_NumberOfParameters = 1;
- };
+ MRFEnergy() :
+ m_NumberOfParameters(1),
+ m_Parameters(0)
+ {};
virtual ~MRFEnergy() {};
unsigned int m_NumberOfParameters;
ParametersType m_Parameters;
@@ -221,11 +221,10 @@ public:
protected:
// The constructor and destructor.
- MRFEnergy()
- {
- m_NumberOfParameters = 1;
- m_Parameters=0;
- };
+ MRFEnergy():
+ m_NumberOfParameters(1),
+ m_Parameters(0)
+ {};
virtual ~MRFEnergy() {};
unsigned int m_NumberOfParameters;
ParametersType m_Parameters;
diff --git a/Code/Markov/otbMRFEnergyEdgeFidelity.h b/Code/Markov/otbMRFEnergyEdgeFidelity.h
index 06511e4380..9ce2940f97 100644
--- a/Code/Markov/otbMRFEnergyEdgeFidelity.h
+++ b/Code/Markov/otbMRFEnergyEdgeFidelity.h
@@ -20,7 +20,6 @@
#define __otbMRFEnergyEdgeFidelity_h
#include "otbMRFEnergy.h"
-#define vnl_math_sqr(x) ((x)*(x))
namespace otb
{
diff --git a/Code/Markov/otbMRFEnergyGaussian.h b/Code/Markov/otbMRFEnergyGaussian.h
index f939bb3bfd..374cfee978 100644
--- a/Code/Markov/otbMRFEnergyGaussian.h
+++ b/Code/Markov/otbMRFEnergyGaussian.h
@@ -23,8 +23,6 @@
#include "otbMath.h"
-#define vnl_math_sqr(x) ((x)*(x))
-
namespace otb
{
/**
diff --git a/Code/Markov/otbMRFEnergyGaussianClassification.h b/Code/Markov/otbMRFEnergyGaussianClassification.h
index d280b5770c..52c0d3b13c 100644
--- a/Code/Markov/otbMRFEnergyGaussianClassification.h
+++ b/Code/Markov/otbMRFEnergyGaussianClassification.h
@@ -21,8 +21,6 @@
#include "otbMRFEnergy.h"
#include "otbMath.h"
-#define vnl_math_sqr(x) ((x)*(x))
-
namespace otb
{
/**
diff --git a/Code/Markov/otbMRFOptimizer.h b/Code/Markov/otbMRFOptimizer.h
index 1b75bfc5dd..ec343eee07 100644
--- a/Code/Markov/otbMRFOptimizer.h
+++ b/Code/Markov/otbMRFOptimizer.h
@@ -67,10 +67,10 @@ public:
virtual bool Compute(double deltaEnergy) = 0;
protected:
- MRFOptimizer()
- {
- m_Parameters=1;
- }
+ MRFOptimizer() :
+ m_NumberOfParameters(1),
+ m_Parameters(1)
+ {}
virtual ~MRFOptimizer() {}
unsigned int m_NumberOfParameters;
ParametersType m_Parameters;
diff --git a/Code/Markov/otbMRFSampler.h b/Code/Markov/otbMRFSampler.h
index be46d94106..e94fd94dde 100644
--- a/Code/Markov/otbMRFSampler.h
+++ b/Code/Markov/otbMRFSampler.h
@@ -94,16 +94,16 @@ protected:
protected:
// The constructor and destructor.
- MRFSampler()
+ MRFSampler():
+ m_NumberOfClasses(1),
+ m_EnergyBefore(1.0),
+ m_EnergyAfter(1.0),
+ m_DeltaEnergy(1.0),
+ m_EnergyCurrent(1.0),
+ m_Lambda(1.0)
{
m_EnergyRegularization = EnergyRegularizationType::New();
- m_EnergyFidelity = EnergyFidelityType::New(),
- m_NumberOfClasses =1;
- m_EnergyBefore = 1.;
- m_EnergyAfter = 1.;
- m_DeltaEnergy = 1.;
- m_EnergyCurrent = 1.;
- m_Lambda = 1.;
+ m_EnergyFidelity = EnergyFidelityType::New();
};
virtual ~MRFSampler() {};
diff --git a/Code/Markov/otbMRFSamplerRandomMAP.h b/Code/Markov/otbMRFSamplerRandomMAP.h
index 1be1680d81..a46218e241 100644
--- a/Code/Markov/otbMRFSamplerRandomMAP.h
+++ b/Code/Markov/otbMRFSamplerRandomMAP.h
@@ -31,7 +31,7 @@ namespace otb
* This is one sampler to be used int he MRF framework. This sampler select the
* value randomly according to the apriori probability.
*
- * The probability is defined from the energy as:
+ * The probability is defined from the energy as:
*
* \f[ P(X=x)= \frac{1}{Z} \exp^{-U(x)} \f]
*
@@ -70,15 +70,15 @@ public:
void SetNumberOfClasses(const unsigned int nClasses)
{
- if (nClasses != this->m_NumberOfClasses || energiesInvalid == true)
+ if (nClasses != this->m_NumberOfClasses || m_EnergiesInvalid == true)
{
this->m_NumberOfClasses = nClasses;
- if (energy != NULL)
- free(energy);
- if (repartitionFunction != NULL)
- free(repartitionFunction);
- energy = (double *) calloc(this->m_NumberOfClasses, sizeof(double));
- repartitionFunction = (double *) calloc(this->m_NumberOfClasses, sizeof(double));
+ if (m_Energy != NULL)
+ free(m_Energy);
+ if (m_RepartitionFunction != NULL)
+ free(m_RepartitionFunction);
+ m_Energy = (double *) calloc(this->m_NumberOfClasses, sizeof(double));
+ m_RepartitionFunction = (double *) calloc(this->m_NumberOfClasses, sizeof(double));
this->Modified();
}
}
@@ -107,9 +107,9 @@ public:
this->m_EnergyCurrent += this->m_Lambda
* this->m_EnergyRegularization->GetValue(itRegul, static_cast<LabelledImagePixelType>(valueCurrent));
- energy[valueCurrent] = this->m_EnergyCurrent;
- repartitionFunction[valueCurrent] = vcl_exp(-this->m_EnergyCurrent)+totalProba;
- totalProba = repartitionFunction[valueCurrent];
+ m_Energy[valueCurrent] = this->m_EnergyCurrent;
+ m_RepartitionFunction[valueCurrent] = vcl_exp(-this->m_EnergyCurrent)+totalProba;
+ totalProba = m_RepartitionFunction[valueCurrent];
}
@@ -118,7 +118,7 @@ public:
//double select = (m_Generator->GetIntegerVariate()/(double(RAND_MAX)+1) * totalProba);
double select = (m_Generator->GetIntegerVariate()/(double(itk::NumericTraits<RandomGeneratorType::IntegerType>::max())+1) * totalProba);
valueCurrent = 0;
- while ( valueCurrent<this->GetNumberOfClasses() && repartitionFunction[valueCurrent] <= select)
+ while ( valueCurrent<this->GetNumberOfClasses() && m_RepartitionFunction[valueCurrent] <= select)
{
valueCurrent++;
}
@@ -132,7 +132,7 @@ public:
if ( this->m_Value != static_cast<LabelledImagePixelType>(valueCurrent))
{
this->m_Value = static_cast<LabelledImagePixelType>(valueCurrent);
- this->m_EnergyAfter = energy[static_cast<unsigned int>(valueCurrent)];
+ this->m_EnergyAfter = m_Energy[static_cast<unsigned int>(valueCurrent)];
}
this->m_DeltaEnergy= this->m_EnergyAfter - this->m_EnergyBefore;
@@ -152,26 +152,26 @@ public:
protected:
// The constructor and destructor.
- MRFSamplerRandomMAP()
+ MRFSamplerRandomMAP():
+ m_RepartitionFunction(NULL),
+ m_Energy(NULL),
+ m_EnergiesInvalid(true)
{
- energy=NULL;
- repartitionFunction=NULL;
- energiesInvalid = true;
m_Generator = RandomGeneratorType::New();
m_Generator->SetSeed();
}
virtual ~MRFSamplerRandomMAP()
{
- if (energy != NULL)
- free(energy);
- if (repartitionFunction != NULL)
- free(repartitionFunction);
+ if (m_Energy != NULL)
+ free(m_Energy);
+ if (m_RepartitionFunction != NULL)
+ free(m_RepartitionFunction);
}
private:
- double * repartitionFunction;
- double * energy;
- bool energiesInvalid;
+ double * m_RepartitionFunction;
+ double * m_Energy;
+ bool m_EnergiesInvalid;
RandomGeneratorType::Pointer m_Generator;
};
}
diff --git a/Code/Markov/otbMarkovRandomFieldFilter.h b/Code/Markov/otbMarkovRandomFieldFilter.h
index 38b8818465..0c2598d98a 100644
--- a/Code/Markov/otbMarkovRandomFieldFilter.h
+++ b/Code/Markov/otbMarkovRandomFieldFilter.h
@@ -367,7 +367,6 @@ protected:
unsigned int m_NumberOfClasses;
unsigned int m_MaximumNumberOfIterations;
- unsigned int m_KernelSize;
int m_ErrorCounter;
double m_ImageDeltaEnergy;
diff --git a/Code/Markov/otbMarkovRandomFieldFilter.txx b/Code/Markov/otbMarkovRandomFieldFilter.txx
index f88bf3bfe1..3ba9992995 100644
--- a/Code/Markov/otbMarkovRandomFieldFilter.txx
+++ b/Code/Markov/otbMarkovRandomFieldFilter.txx
@@ -22,10 +22,9 @@
namespace otb
{
-/** ATTENTION : j'ai passe les initialisation dans le constructeur car certaines plateformes (dont NEMO) n'aiment cette maniere d'initialiser*/
template<class TInputImage, class TClassifiedImage>
MarkovRandomFieldFilter<TInputImage,TClassifiedImage>
-::MarkovRandomFieldFilter(void)/* :
+::MarkovRandomFieldFilter(void) :
m_NumberOfClasses(0),
m_MaximumNumberOfIterations(50),
m_ErrorCounter(0),
@@ -34,24 +33,12 @@ MarkovRandomFieldFilter<TInputImage,TClassifiedImage>
m_TotalNumberOfValidPixelsInOutputImage(1),
m_TotalNumberOfPixelsInInputImage(1),
m_ErrorTolerance(0.0),
- m_SmoothingFactor(1),
+ m_SmoothingFactor(1.0),
m_NumberOfIterations(0),
- m_StopCondition(MaximumNumberOfIterations),
- m_ExternalClassificationSet(false)
- */
+ m_Lambda(1.0),
+ m_ExternalClassificationSet(false),
+ m_StopCondition(MaximumNumberOfIterations)
{
- m_NumberOfClasses = 0;
- m_MaximumNumberOfIterations = 50;
- m_ErrorCounter = 0;
- m_ImageDeltaEnergy = 0.0;
- m_NeighborhoodRadius = 1;
- m_TotalNumberOfValidPixelsInOutputImage = 1;
- m_TotalNumberOfPixelsInInputImage = 1;
- m_ErrorTolerance = 0.0;
- m_SmoothingFactor = 1;
- m_NumberOfIterations = 0;
- m_StopCondition = MaximumNumberOfIterations;
- m_ExternalClassificationSet = false;
m_Generator = RandomGeneratorType::New();
m_Generator->SetSeed();
--
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