Commit b3d519db authored by OTB Bot's avatar OTB Bot

STYLE

parent f5725948
......@@ -27,12 +27,12 @@ namespace otb {
/** \class AngularProjectionBinaryImageFilter
* \brief Performs \f$ y_i = \cos \theta_i x_1 + \sin \theta_i x_2\f$
*
* This class performs the projections of the 2 input images to a set of N
* This class performs the projections of the 2 input images to a set of N
* output images according to N angular values
*
*/
template < class TInputImage, class TOutputImage, class TPrecision >
class ITK_EXPORT AngularProjectionBinaryImageFilter
class ITK_EXPORT AngularProjectionBinaryImageFilter
: public itk::ImageToImageFilter< TInputImage, TOutputImage >
{
public:
......
......@@ -38,7 +38,7 @@ void
AngularProjectionBinaryImageFilter< TInputImage, TOutputImage, TPrecision >
::SetInput1 ( const InputImageType * inputPtr )
{
this->SetNthInput(0,const_cast<InputImageType*>( inputPtr ));
this->SetNthInput(0, const_cast<InputImageType*>( inputPtr ));
}
template < class TInputImage, class TOutputImage, class TPrecision >
......@@ -46,7 +46,7 @@ void
AngularProjectionBinaryImageFilter< TInputImage, TOutputImage, TPrecision >
::SetInput2 ( const InputImageType * inputPtr )
{
this->SetNthInput(1,const_cast<InputImageType*>( inputPtr ));
this->SetNthInput(1, const_cast<InputImageType*>( inputPtr ));
}
template < class TInputImage, class TOutputImage, class TPrecision >
......@@ -105,7 +105,7 @@ AngularProjectionBinaryImageFilter< TInputImage, TOutputImage, TPrecision >
template < class TInputImage, class TOutputImage, class TPrecision >
void
AngularProjectionBinaryImageFilter< TInputImage, TOutputImage, TPrecision >
::ThreadedGenerateData
::ThreadedGenerateData
( const OutputImageRegionType & outputRegionForThread, int threadId )
{
itk::ProgressReporter reporter(this, threadId,
......@@ -122,11 +122,11 @@ AngularProjectionBinaryImageFilter< TInputImage, TOutputImage, TPrecision >
( this->GetInput2(), inputRegionForThread );
iter2.GoToBegin();
std::vector< itk::ImageRegionIterator<OutputImageType> > outIter
( this->GetNumberOfOutputs() );
std::vector< itk::ImageRegionIterator<OutputImageType> > outIter
( this->GetNumberOfOutputs() );
for ( unsigned int i = 0; i < outIter.size(); i++ )
{
outIter[i] = itk::ImageRegionIterator<OutputImageType>
outIter[i] = itk::ImageRegionIterator<OutputImageType>
( this->GetOutput(i), outputRegionForThread );
outIter[i].GoToBegin();
}
......@@ -147,7 +147,7 @@ AngularProjectionBinaryImageFilter< TInputImage, TOutputImage, TPrecision >
}
}
} // end of namespace otb
} // end of namespace otb
#endif
......
......@@ -31,11 +31,11 @@ namespace otb {
* \brief Generate join sample from 2 set of ImageList
*
* This class transform the initial data contained in 2 imageList to
* yield a set of join sample \f$(x_i,y_i)\f$ or a set of parameters
* yield a set of join sample \f$(x_i, y_i)\f$ or a set of parameters
* extracted from the 2 image lists.
*
* The Function gives the possibility to select some of the samples only
* and to transform the output data. Hence, the functor should have also a IsToGenerate
* The Function gives the possibility to select some of the samples only
* and to transform the output data. Hence, the functor should have also a IsToGenerate
* boolean function...
*
* This filter provides pipeline support for itk::Statistics::ListSample via
......@@ -140,7 +140,7 @@ private:
void operator=(const Self &); // not implemeted
FunctorType m_Functor;
}; // end of class
}; // end of class
} // end of namespace otb
......@@ -148,5 +148,5 @@ private:
#include "otbBinaryFunctorImageListToSampleListFilter.txx"
#endif
#endif
#endif
......@@ -54,7 +54,7 @@ typename BinaryFunctorImageListToSampleListFilter< TInputImageList, TOutputSampl
BinaryFunctorImageListToSampleListFilter< TInputImageList, TOutputSampleList, TFunction >
::GetOutputSampleList()
{
typename OutputSampleListObjectType::Pointer dataObjectPointer
typename OutputSampleListObjectType::Pointer dataObjectPointer
= static_cast<OutputSampleListObjectType * > (this->ProcessObject::GetOutput(0) );
return const_cast<OutputSampleListType *>(dataObjectPointer->Get());
}
......@@ -142,7 +142,7 @@ BinaryFunctorImageListToSampleListFilter< TInputImageList, TOutputSampleList, TF
// Set-up progress reporting
itk::ProgressReporter progress(this, 0, list1->Size());
while ( listIterator1 != list1->End()
while ( listIterator1 != list1->End()
&& listIterator2 != list2->End() )
{
InputImageType * img1 = listIterator1.Get();
......@@ -177,4 +177,3 @@ BinaryFunctorImageListToSampleListFilter< TInputImageList, TOutputSampleList, TF
......@@ -23,7 +23,7 @@
#include "otbMatrixImageFilter.h"
#include "otbStreamingStatisticsVectorImageFilter.h"
namespace otb
namespace otb
{
/** \class FastICAInternalOptimizerVectorImageFilter
* \brief Internal optimisation of the FastICA unmixing filter
......@@ -31,7 +31,7 @@ namespace otb
* This class implements the internal search for the unmixing matrix W
* in the FastICA technique.
*
* The class takes 2 inputs (initial image and its projection with the W matrix).
* The class takes 2 inputs (initial image and its projection with the W matrix).
*
* \ingroup Multithreaded
* \sa FastICAImageFilter
......@@ -80,15 +80,15 @@ public:
typedef double (*ContrastFunctionType) ( double );
itkSetMacro(CurrentBandForLoop,unsigned int);
itkGetMacro(CurrentBandForLoop,unsigned int);
itkSetMacro(CurrentBandForLoop, unsigned int);
itkGetMacro(CurrentBandForLoop, unsigned int);
itkGetMacro(W,InternalMatrixType);
itkSetMacro(W,InternalMatrixType);
itkGetMacro(W, InternalMatrixType);
itkSetMacro(W, InternalMatrixType);
itkSetMacro(ContrastFunction,ContrastFunctionType);
itkGetMacro(Beta,double);
itkGetMacro(Den,double);
itkSetMacro(ContrastFunction, ContrastFunctionType);
itkGetMacro(Beta, double);
itkGetMacro(Den, double);
protected:
FastICAInternalOptimizerVectorImageFilter();
......
......@@ -79,7 +79,7 @@ FastICAInternalOptimizerVectorImageFilter< TInputImage, TOutputImage >
InputRegionType inputRegion;
this->CallCopyOutputRegionToInputRegion( inputRegion, outputRegionForThread );
itk::ImageRegionConstIterator< InputImageType > input0It
itk::ImageRegionConstIterator< InputImageType > input0It
( this->GetInput(0), inputRegion );
itk::ImageRegionConstIterator< InputImageType > input1It
( this->GetInput(1), inputRegion );
......@@ -148,4 +148,3 @@ FastICAInternalOptimizerVectorImageFilter< TInputImage, TOutputImage >
#endif
......@@ -58,15 +58,15 @@ public:
template < class TInputImage, class TOutputImage >
class ITK_EXPORT HorizontalSobelVectorImageFilter
: public UnaryFunctorNeighborhoodVectorImageFilter< TInputImage, TOutputImage,
Functor::HorizontalSobelOperator<
Functor::HorizontalSobelOperator<
typename itk::ConstNeighborhoodIterator<TInputImage>,
typename TOutputImage::PixelType > >
typename TOutputImage::PixelType > >
{
public:
/** Standart class typedefs */
typedef HorizontalSobelVectorImageFilter Self;
typedef UnaryFunctorNeighborhoodVectorImageFilter< TInputImage, TOutputImage,
Functor::HorizontalSobelOperator<
Functor::HorizontalSobelOperator<
typename itk::ConstNeighborhoodIterator<TInputImage>,
typename TOutputImage::PixelType > > Superclass;
typedef itk::SmartPointer<Self> Pointer;
......@@ -81,7 +81,7 @@ public:
protected:
HorizontalSobelVectorImageFilter()
{
typename Superclass::RadiusType radius = {{1,1}};
typename Superclass::RadiusType radius = {{1, 1}};
SetRadius( radius );
}
virtual ~HorizontalSobelVectorImageFilter() { }
......
......@@ -47,14 +47,14 @@ public:
unsigned int neighborSize = input.Size();
unsigned int vectorSize = centerPixel.Size();
if ( neighborSize == 1 )
if ( neighborSize == 1 )
return centerPixel;
TOutput output ( vectorSize );
for ( unsigned int i = 0; i < vectorSize; i++ )
{
typename TOutput::ValueType out
typename TOutput::ValueType out
= itk::NumericTraits< typename TOutput::ValueType >::Zero;
for ( unsigned int j = 0; j < neighborSize/2; j++ )
{
......@@ -80,15 +80,15 @@ public:
template < class TInputImage, class TOutputImage >
class ITK_EXPORT LocalActivityVectorImageFilter
: public UnaryFunctorNeighborhoodVectorImageFilter< TInputImage, TOutputImage,
Functor::LocalActivityOperator<
Functor::LocalActivityOperator<
typename itk::ConstNeighborhoodIterator<TInputImage>,
typename TOutputImage::PixelType > >
typename TOutputImage::PixelType > >
{
public:
/** Standart class typedefs */
typedef LocalActivityVectorImageFilter Self;
typedef UnaryFunctorNeighborhoodVectorImageFilter< TInputImage, TOutputImage,
Functor::LocalActivityOperator<
Functor::LocalActivityOperator<
typename itk::ConstNeighborhoodIterator<TInputImage>,
typename TOutputImage::PixelType > > Superclass;
typedef itk::SmartPointer<Self> Pointer;
......
......@@ -47,7 +47,7 @@ public:
for ( unsigned int i = 0; i < length; i++ )
{
output[i] = static_cast<typename TOutput::ValueType>(
input.GetCenterPixel()[i]
input.GetCenterPixel()[i]
- input.GetPixel(5)[i] / 2.
- input.GetPixel(7)[i] / 2. );
}
......@@ -63,15 +63,15 @@ public:
template < class TInputImage, class TOutputImage >
class ITK_EXPORT LocalGradientVectorImageFilter
: public UnaryFunctorNeighborhoodVectorImageFilter< TInputImage, TOutputImage,
Functor::LocalGradientOperator<
Functor::LocalGradientOperator<
typename itk::ConstNeighborhoodIterator<TInputImage>,
typename TOutputImage::PixelType > >
typename TOutputImage::PixelType > >
{
public:
/** Standart class typedefs */
typedef LocalGradientVectorImageFilter Self;
typedef UnaryFunctorNeighborhoodVectorImageFilter< TInputImage, TOutputImage,
Functor::LocalGradientOperator<
Functor::LocalGradientOperator<
typename itk::ConstNeighborhoodIterator<TInputImage>,
typename TOutputImage::PixelType > > Superclass;
typedef itk::SmartPointer<Self> Pointer;
......@@ -84,10 +84,10 @@ public:
itkTypeMacro(LocalGradientVectorImageFilter, ImageToImageFilter);
protected:
LocalGradientVectorImageFilter()
LocalGradientVectorImageFilter()
{
typename Superclass::RadiusType radius = {{1,1}};
SetRadius( radius );
typename Superclass::RadiusType radius = {{1, 1}};
SetRadius( radius );
}
virtual ~LocalGradientVectorImageFilter() { }
......
......@@ -31,7 +31,7 @@ namespace otb {
/** \class MNFImageFilter
* \brief Performs a Minimum Noise Fraction analysis of a vector image.
*
* The internal structure of this filter is a filter-to-filter like structure.
* The internal structure of this filter is a filter-to-filter like structure.
* The estimation of the covariance matrix has persistent capabilities...
*
* The high pass filter which has to be used for the noise estimation is templated
......@@ -42,10 +42,10 @@ namespace otb {
* \sa otbStreamingStatisticsVectorImageFilter
* \sa PCAImageFiler
*/
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
Transform::TransformDirection TDirectionOfTransformation >
class ITK_EXPORT MNFImageFilter
class ITK_EXPORT MNFImageFilter
: public itk::ImageToImageFilter<TInputImage, TOutputImage>
{
public:
......@@ -66,7 +66,7 @@ public:
itkStaticConstMacro(OutputImageDimension, unsigned int, TOutputImage::ImageDimension);
typedef Transform::TransformDirection TransformDirectionEnumType;
itkStaticConstMacro(DirectionOfTransformation,TransformDirectionEnumType,TDirectionOfTransformation);
itkStaticConstMacro(DirectionOfTransformation, TransformDirectionEnumType, TDirectionOfTransformation);
/** Template parameters typedefs */
typedef TInputImage InputImageType;
......@@ -92,30 +92,30 @@ public:
typedef NormalizeVectorImageFilter< InputImageType, OutputImageType > NormalizeFilterType;
typedef typename NormalizeFilterType::Pointer NormalizeFilterPointerType;
/**
* Set/Get the number of required largest principal components.
/**
* Set/Get the number of required largest principal components.
*/
itkGetMacro(NumberOfPrincipalComponentsRequired,unsigned int);
itkSetMacro(NumberOfPrincipalComponentsRequired,unsigned int);
itkGetMacro(NumberOfPrincipalComponentsRequired, unsigned int);
itkSetMacro(NumberOfPrincipalComponentsRequired, unsigned int);
itkGetConstMacro(Normalizer,NormalizeFilterType*);
itkGetMacro(Normalizer,NormalizeFilterType*);
itkGetConstMacro(Normalizer, NormalizeFilterType*);
itkGetMacro(Normalizer, NormalizeFilterType*);
itkGetMacro(NoiseCovarianceEstimator, CovarianceEstimatorFilterType *);
itkGetMacro(Transformer, TransformFilterType *);
itkGetMacro(NoiseImageFilter, NoiseImageFilterType *);
/** Normalization only impact the use of variance. The data is always centered */
itkGetMacro(UseNormalization,bool);
itkSetMacro(UseNormalization,bool);
itkGetMacro(UseNormalization, bool);
itkSetMacro(UseNormalization, bool);
itkGetConstMacro(MeanValues,VectorType);
itkGetConstMacro(MeanValues, VectorType);
void SetMeanValues ( const VectorType & vec )
{
m_MeanValues = vec;
m_GivenMeanValues = true;
}
itkGetConstMacro(StdDevValues,VectorType);
itkGetConstMacro(StdDevValues, VectorType);
void SetStdDevValues ( const VectorType & vec )
{
m_StdDevValues = vec;
......@@ -123,7 +123,7 @@ public:
m_GivenStdDevValues = true;
}
itkGetConstMacro(CovarianceMatrix,MatrixType);
itkGetConstMacro(CovarianceMatrix, MatrixType);
void SetCovarianceMatrix ( const MatrixType & cov )
{
m_CovarianceMatrix = cov;
......@@ -137,7 +137,7 @@ public:
m_GivenNoiseCovarianceMatrix = true;
}
itkGetConstMacro(TransformationMatrix,MatrixType);
itkGetConstMacro(TransformationMatrix, MatrixType);
void SetTransformationMatrix( const MatrixType & transf, bool isForward = true )
{
m_TransformationMatrix = transf;
......@@ -145,17 +145,17 @@ public:
m_IsTransformationMatrixForward = isForward;
}
itkGetConstMacro(EigenValues,VectorType);
itkGetConstMacro(EigenValues, VectorType);
protected:
MNFImageFilter();
virtual ~MNFImageFilter() { }
/** GenerateOutputInformation
* Propagate vector length info and modify if needed
* Propagate vector length info and modify if needed
* NumberOfPrincipalComponentsRequired
*
* In REVERSE mode, the covariance matrix or the transformation matrix
* In REVERSE mode, the covariance matrix or the transformation matrix
* (which may not be square) has to be given,
* otherwize, GenerateOutputInformation throws an itk::ExceptionObject
*/
......@@ -215,4 +215,3 @@ private:
#endif
......@@ -28,8 +28,8 @@
namespace otb
{
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
Transform::TransformDirection TDirectionOfTransformation >
MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransformation >
::MNFImageFilter ()
......@@ -55,8 +55,8 @@ MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransf
m_Transformer->MatrixByVectorOn();
}
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
Transform::TransformDirection TDirectionOfTransformation >
void
MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransformation >
......@@ -69,11 +69,11 @@ MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransf
{
case Transform::FORWARD:
{
if ( m_NumberOfPrincipalComponentsRequired == 0
|| m_NumberOfPrincipalComponentsRequired
if ( m_NumberOfPrincipalComponentsRequired == 0
|| m_NumberOfPrincipalComponentsRequired
> this->GetInput()->GetNumberOfComponentsPerPixel() )
{
m_NumberOfPrincipalComponentsRequired =
m_NumberOfPrincipalComponentsRequired =
this->GetInput()->GetNumberOfComponentsPerPixel();
}
......@@ -113,8 +113,8 @@ MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransf
}
}
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
Transform::TransformDirection TDirectionOfTransformation >
void
MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransformation >
......@@ -133,14 +133,14 @@ MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransf
}
}
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
Transform::TransformDirection TDirectionOfTransformation >
void
MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransformation >
::ForwardGenerateData ()
{
typename InputImageType::Pointer inputImgPtr
typename InputImageType::Pointer inputImgPtr
= const_cast<InputImageType*>( this->GetInput() );
if ( m_GivenMeanValues )
......@@ -218,8 +218,8 @@ MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransf
}
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
Transform::TransformDirection TDirectionOfTransformation >
void
MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransformation >
......@@ -308,7 +308,7 @@ MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransf
{
VectorType revMean ( m_MeanValues.Size() );
for ( unsigned int i = 0; i < m_MeanValues.Size(); i++ )
revMean[i] = - m_MeanValues[i] ;
revMean[i] = - m_MeanValues[i];
m_Normalizer->SetMean( revMean );
m_Normalizer->SetUseStdDev( false );
}
......@@ -320,8 +320,8 @@ MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransf
this->GraftOutput( m_Normalizer->GetOutput() );
}
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
Transform::TransformDirection TDirectionOfTransformation >
void
MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransformation >
......@@ -340,14 +340,14 @@ MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransf
for ( unsigned int i = 0; i < transf.rows(); i++ )
{
double norm = 1. / vcl_sqrt( normMat.get(i,i) );
double norm = 1. / vcl_sqrt( normMat.get(i, i) );
for ( unsigned int j = 0; j < transf.cols(); j++ )
transf.put( j, i, transf.get(j,i) * norm );
transf.put( j, i, transf.get(j, i) * norm );
}
transf.inplace_transpose();
if ( m_NumberOfPrincipalComponentsRequired
if ( m_NumberOfPrincipalComponentsRequired
!= this->GetInput()->GetNumberOfComponentsPerPixel() )
m_TransformationMatrix = transf.get_n_rows( 0, m_NumberOfPrincipalComponentsRequired );
else
......@@ -355,11 +355,11 @@ MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransf
m_EigenValues.SetSize( m_NumberOfPrincipalComponentsRequired );
for ( unsigned int i = 0; i < m_NumberOfPrincipalComponentsRequired; i++ )
m_EigenValues[i] = static_cast< RealType >( valP(i,i) );
m_EigenValues[i] = static_cast< RealType >( valP(i, i) );
}
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
Transform::TransformDirection TDirectionOfTransformation >
void
MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransformation >
......
......@@ -32,7 +32,7 @@ namespace otb
* The awaited type must be compatible with vnl_matrix<double>
*
* The multiplication can be done as \f$ p . M \f$ or \f$ M . p \f$ where \f$ p \f$ is the pixel and \f$ M \f$ is the vector.
* The behavior can be chosen with
* The behavior can be chosen with
*
* The number of rows of the matrix must be the input image number of channels, the number of columns is the number of channels of the output image.
*
......@@ -132,7 +132,7 @@ private:
/** Matrix declaration */
MatrixType m_Matrix;
/** If set to true, the applied operation is \f$ M . p \f$ where p is the pixel represented as a column vector.
/** If set to true, the applied operation is \f$ M . p \f$ where p is the pixel represented as a column vector.
Otherwise the applied operation is \f$ p . M \f$ where p is the pixel represented as a row vector.
*/
bool m_MatrixByVector;
......
......@@ -25,13 +25,13 @@ namespace otb {
/** \class NAPCAImageFilter
* \brief Performs a Noise Adjusted PCA analysis of a vector image.
*
* The internal structure of this filter is a filter-to-filter like structure.
* The internal structure of this filter is a filter-to-filter like structure.
* The estimation of the covariance matrix has persistent capabilities...
*
* The high pass filter which has to be used for the noise estimation is templated
* for a better scalability...
*
* This class is very similar to the MNFImageFilter one since only the projection
* This class is very similar to the MNFImageFilter one since only the projection
* matrix definition (through GenerateTransformationMatrix function)
* differs.
*
......@@ -40,15 +40,15 @@ namespace otb {
* \sa otbStreamingStatisticsVectorImageFilter
* \sa MNFImageFilter
*/
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
Transform::TransformDirection TDirectionOfTransformation >
class ITK_EXPORT NAPCAImageFilter
class ITK_EXPORT NAPCAImageFilter
: public MNFImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransformation >
{
public:
typedef NAPCAImageFilter Self;
typedef MNFImageFilter< TInputImage, TOutputImage,
typedef MNFImageFilter< TInputImage, TOutputImage,
TNoiseImageFilter, TDirectionOfTransformation > Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
......@@ -57,7 +57,7 @@ public:
itkNewMacro(Self);
/** Creation through object factory macro */
itkTypeMacro(NAPCAImageFilter,MNFImageFilter);
itkTypeMacro(NAPCAImageFilter, MNFImageFilter);
/** Template parameters typedefs */
typedef typename Superclass::InputImageType InputImageType;
......
......@@ -25,11 +25,11 @@
#include <vnl/algo/vnl_matrix_inverse.h>
#include <vnl/algo/vnl_generalized_eigensystem.h>
namespace otb
namespace otb
{
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
template <class TInputImage, class TOutputImage,
class TNoiseImageFilter,
Transform::TransformDirection TDirectionOfTransformation >
void
NAPCAImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTransformation >
......@@ -52,7 +52,7 @@ NAPCAImageFilter< TInputImage, TOutputImage, TNoiseImageFilter, TDirectionOfTran
transf.fliplr();
transf.inplace_transpose();