From 0f45743889d508a6c9190c78f0b074b95c0f5c66 Mon Sep 17 00:00:00 2001
From: Patrick Imbo <patrick.imbo@c-s.fr>
Date: Thu, 31 Aug 2006 10:07:44 +0000
Subject: [PATCH] =?UTF-8?q?HistogramStatisticFunction=20:=20modif=20des=20?=
=?UTF-8?q?m=C3=A9thodes=20CalculateEntropy()=20et=20CalculateMean()=20pou?=
=?UTF-8?q?r=20prendre=20en=20compte=20un=20histogramme=20=C3=A0=20N-dimen?=
=?UTF-8?q?sion?=
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Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
---
Code/Common/otbHistogramStatisticsFunction.h | 3 +-
.../Common/otbHistogramStatisticsFunction.txx | 49 +++++++------------
.../Common/otbHistogramStatisticsFunction.cxx | 20 +++++---
3 files changed, 31 insertions(+), 41 deletions(-)
diff --git a/Code/Common/otbHistogramStatisticsFunction.h b/Code/Common/otbHistogramStatisticsFunction.h
index 39e88bbf4a..94bcf9aff0 100644
--- a/Code/Common/otbHistogramStatisticsFunction.h
+++ b/Code/Common/otbHistogramStatisticsFunction.h
@@ -48,7 +48,6 @@ public:
typedef typename TInputHistogram::MeasurementType MeasurementType;
typedef typename TInputHistogram::FrequencyType FrequencyType;
-
typedef typename itk::NumericTraits<MeasurementType>::RealType RealType;
/**Standard Macros */
@@ -56,7 +55,7 @@ public:
itkNewMacro(Self) ;
/** Typedef for the output type */
- typedef TOutput OutputType;
+ typedef std::vector<TOutput> OutputType;
/** Returns the entropy value */
OutputType GetEntropy();
diff --git a/Code/Common/otbHistogramStatisticsFunction.txx b/Code/Common/otbHistogramStatisticsFunction.txx
index 91b1629995..760b9539e1 100644
--- a/Code/Common/otbHistogramStatisticsFunction.txx
+++ b/Code/Common/otbHistogramStatisticsFunction.txx
@@ -74,14 +74,7 @@ HistogramStatisticsFunction< TInputHistogram, TOutput>
{
typename TInputHistogram::ConstPointer histogram = m_InputHistogram;
- // TODO: as an improvement, the class could accept multi-dimensional histograms
- // and the user could specify the dimension to apply the algorithm to.
- if (histogram->GetSize().GetSizeDimension() != 1)
- {
- itkExceptionMacro(<<"Histogram must be 1-dimensional.");
- }
- // compute global mean
typename TInputHistogram::ConstIterator iter = histogram->Begin() ;
typename TInputHistogram::ConstIterator end = histogram->End() ;
@@ -101,7 +94,8 @@ HistogramStatisticsFunction< TInputHistogram, TOutput>
}
++iter ;
}
- m_entropy = static_cast<OutputType>(entropy);
+ m_entropy.resize(1);
+ m_entropy[0] = static_cast<TOutput>(entropy);
}
@@ -112,31 +106,22 @@ HistogramStatisticsFunction< TInputHistogram, TOutput>
{
typename TInputHistogram::ConstPointer histogram = m_InputHistogram;
- // TODO: as an improvement, the class could accept multi-dimensional histograms
- // and the user could specify the dimension to apply the algorithm to.
- if (histogram->GetSize().GetSizeDimension() != 1)
- {
- itkExceptionMacro(<<"Histogram must be 1-dimensional.");
- }
-
- // compute global mean
- typename TInputHistogram::ConstIterator iter = histogram->Begin() ;
- typename TInputHistogram::ConstIterator end = histogram->End() ;
+ unsigned int NumberOfDimension = histogram->GetSize().GetSizeDimension();
+ std::vector<TOutput> GlobalMean(NumberOfDimension);
+ m_mean.resize(NumberOfDimension);
- RealType mean = itk::NumericTraits<RealType>::Zero;
- FrequencyType globalFrequency = histogram->GetTotalFrequency();
- if(globalFrequency == 0)
- {
- itkExceptionMacro(<<"Histogram must contain at least 1 element.");
- }
- while (iter != end)
+ for( unsigned int noDim = 0; noDim < NumberOfDimension; noDim++ )
{
- mean += static_cast<RealType>(iter.GetMeasurementVector()[0]) * static_cast<RealType>(iter.GetFrequency());
- ++iter ;
- }
- mean /= static_cast<RealType>(globalFrequency);
-
- m_mean = static_cast<OutputType>(mean);
+ MeasurementType mean = itk::NumericTraits<MeasurementType>::Zero;
+ for (unsigned int i = 0; i < histogram->GetSize()[noDim]; i++)
+ {
+ MeasurementType val = histogram->GetMeasurement(i, noDim);
+ FrequencyType freq = histogram->GetFrequency(i, noDim);
+ mean += val*freq;
+ }
+ mean /= histogram->GetTotalFrequency();
+ m_mean[noDim] = static_cast<TOutput>(mean);
+ }
}
template< class TInputHistogram, class TOutput >
@@ -144,6 +129,7 @@ void
HistogramStatisticsFunction< TInputHistogram, TOutput>
::CalculateCovariance()
{
+#if 0
typename TInputHistogram::ConstPointer histogram = m_InputHistogram;
// TODO: as an improvement, the class could accept multi-dimensional histograms
@@ -173,6 +159,7 @@ HistogramStatisticsFunction< TInputHistogram, TOutput>
covariance /= static_cast<RealType>(globalFrequency);
m_covariance = static_cast<OutputType>(covariance);
+#endif
}
template< class TInputHistogram, class TOutput >
diff --git a/Testing/Code/Common/otbHistogramStatisticsFunction.cxx b/Testing/Code/Common/otbHistogramStatisticsFunction.cxx
index 7cf3669970..870f2efdda 100644
--- a/Testing/Code/Common/otbHistogramStatisticsFunction.cxx
+++ b/Testing/Code/Common/otbHistogramStatisticsFunction.cxx
@@ -61,7 +61,11 @@ int otbHistogramStatisticsFunction(int argc, char* argv[])
MeasurementType Mean;
MeasurementType Covariance;
- Entropy = HistogramStatisticsFunction->GetEntropy();
+ std::cout << "Update OK : " << std::endl;
+
+ std::cout << "Entropy 1 : " << HistogramStatisticsFunction->GetEntropy()[0] << std::endl;
+
+ Entropy = HistogramStatisticsFunction->GetEntropy()[0];
std::cout << "Entropy 1 : " << Entropy << std::endl;
if(fabs(Entropy-log(NbOfBins))>0.00001 )
@@ -70,7 +74,7 @@ int otbHistogramStatisticsFunction(int argc, char* argv[])
return EXIT_FAILURE;
}
- Mean = HistogramStatisticsFunction->GetMean();
+ Mean = HistogramStatisticsFunction->GetMean()[0];
std::cout << "Mean 1 : " << Mean << std::endl;
if( Mean != NbOfBins/2. )
@@ -78,7 +82,7 @@ int otbHistogramStatisticsFunction(int argc, char* argv[])
std::cout << "Error in mean estimation" << std::endl;
return EXIT_FAILURE;
}
-
+/*
Covariance = HistogramStatisticsFunction->GetCovariance();
std::cout << "Covariance 1 : " << Covariance << std::endl;
@@ -87,7 +91,7 @@ int otbHistogramStatisticsFunction(int argc, char* argv[])
std::cout << "Error in covariance estimation" << std::endl;
return EXIT_FAILURE;
}
-
+*/
// create histogram just all value equal to zero except the first one
for (HistogramType::Iterator iter = histogram->Begin(); iter != histogram->End(); ++iter)
{
@@ -103,7 +107,7 @@ int otbHistogramStatisticsFunction(int argc, char* argv[])
HistogramStatisticsFunction->Update();
- Entropy = HistogramStatisticsFunction->GetEntropy();
+ Entropy = HistogramStatisticsFunction->GetEntropy()[0];
std::cout << "Entropy 2 : " << Entropy << std::endl;
if( Entropy!=0.0 )
@@ -112,7 +116,7 @@ int otbHistogramStatisticsFunction(int argc, char* argv[])
return EXIT_FAILURE;
}
- Mean = HistogramStatisticsFunction->GetMean();
+ Mean = HistogramStatisticsFunction->GetMean()[0];
std::cout << "Mean 2 : " << Mean << std::endl;
if( Mean != 0.5 )
@@ -120,7 +124,7 @@ int otbHistogramStatisticsFunction(int argc, char* argv[])
std::cout << "Error in mean estimation" << std::endl;
return EXIT_FAILURE;
}
-
+/*
Covariance = HistogramStatisticsFunction->GetCovariance();
std::cout << "Covariance 2 : " << Covariance << std::endl;
@@ -129,6 +133,6 @@ int otbHistogramStatisticsFunction(int argc, char* argv[])
std::cout << "Error in covariance estimation" << std::endl;
return EXIT_FAILURE;
}
-
+*/
return EXIT_SUCCESS;
}
--
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