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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 otbNAPCAImageFilter_txx
#define otbNAPCAImageFilter_txx
#include "otbNAPCAImageFilter.h"
#include "itkMacro.h"
#include <vnl/vnl_matrix.h>
#include <vnl/algo/vnl_matrix_inverse.h>
#include <vnl/algo/vnl_symmetric_eigensystem.h>
#include <vnl/algo/vnl_generalized_eigensystem.h>
namespace otb
{
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
Transform::TransformDirection TDirectionOfTransformation >
void
NAPCAImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransformation >
::GenerateTransformationMatrix ()
{
InternalMatrixType An = this->GetNoiseCovarianceMatrix().GetVnlMatrix();
InternalMatrixType Fn;
vnl_vector<double> vectValPn;
vnl_symmetric_eigensystem_compute( An, Fn, vectValPn );
/* We used normalized PCA */
InternalMatrixType valPn ( vectValPn.size(), vectValPn.size(), vnl_matrix_null );
for ( unsigned int i = 0; i < valPn.rows(); ++i )
{
if ( vectValPn[i] > 0. )
{
valPn(i, i) = 1. / vcl_sqrt( vectValPn[i] );
}
else if ( vectValPn[i] < 0. )
{
otbMsgDebugMacro( << "ValPn(" << i << ") neg : " << vectValPn[i] << " taking abs value" );
valPn(i, i) = 1. / vcl_sqrt( vcl_abs( vectValPn[i] ) );
}
else
{
throw itk::ExceptionObject( __FILE__, __LINE__,
"Null Eigen value !!", ITK_LOCATION );
}
}
Fn = Fn * valPn;
InternalMatrixType Ax
= vnl_matrix_inverse< MatrixElementType > ( this->GetCovarianceMatrix().GetVnlMatrix() );
InternalMatrixType Aadj = Fn.transpose() * Ax * Fn;
InternalMatrixType Fadj;
vnl_vector<double> vectValPadj;
vnl_symmetric_eigensystem_compute( Aadj, Fadj, vectValPadj );
InternalMatrixType transf = Fn * Fadj;
transf.inplace_transpose();
if ( this->GetNumberOfPrincipalComponentsRequired()
!= this->GetInput()->GetNumberOfComponentsPerPixel() )
this->m_TransformationMatrix = transf.get_n_rows( 0, this->GetNumberOfPrincipalComponentsRequired() );
else
this->m_TransformationMatrix = transf;
this->m_EigenValues.SetSize( this->GetNumberOfPrincipalComponentsRequired() );
for ( unsigned int i = 0; i < this->GetNumberOfPrincipalComponentsRequired(); ++i )
this->m_EigenValues[this->GetNumberOfPrincipalComponentsRequired()-1-i]
= static_cast< RealType >( vectValPadj[i] );
}
} // end of namespace otb
#endif
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