itkGaussianBlurImageFunction.txx

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/*=========================================================================

  Program:   Insight Segmentation & Registration Toolkit
  Module:    $RCSfile: itkGaussianBlurImageFunction.txx,v $
  Language:  C++
  Date:      $Date: 2009-06-17 14:43:50 $
  Version:   $Revision: 1.15 $

  Copyright (c) Insight Software Consortium. All rights reserved.
  See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.

     This software is distributed WITHOUT ANY WARRANTY; without even
     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
     PURPOSE.  See the above copyright notices for more information.

=========================================================================*/
#ifndef __itkGaussianBlurImageFunction_txx
#define __itkGaussianBlurImageFunction_txx

#include "itkGaussianBlurImageFunction.h"
#include "itkImageLinearIteratorWithIndex.h"

namespace itk
{

template <class TInputImage,class TOutput>
GaussianBlurImageFunction<TInputImage,TOutput>
::GaussianBlurImageFunction()
{
  typename GaussianFunctionType::ArrayType mean;
  mean[0]=0.0f;
  for(unsigned int i=0;i<itkGetStaticConstMacro(ImageDimension);i++)
    {
    m_Sigma[i] = 1.0f;
    m_MaximumError[i] = 0.001f;
    m_MaximumKernelWidth = 32;
    m_Extent[i] = 1.0f;
    }
  m_UseImageSpacing = true;

  m_GaussianFunction = GaussianFunctionType::New();
  m_GaussianFunction->SetMean(mean);
  m_GaussianFunction->SetNormalized(false); // faster
  m_OperatorImageFunction = OperatorImageFunctionType::New();
  m_InternalImage = InternalImageType::New();
  this->RecomputeGaussianKernel();
  m_Caster = CastImageFilterType::New();
}

template <class TInputImage,class TOutput>
void
GaussianBlurImageFunction<TInputImage,TOutput>
::SetInputImage( const InputImageType * ptr )
{
  Superclass::SetInputImage(ptr);
  m_Caster->SetInput(ptr);
  m_Caster->Update();
  m_OperatorImageFunction->SetInputImage(m_Caster->GetOutput());
}


template <class TInputImage,class TOutput>
void
GaussianBlurImageFunction<TInputImage,TOutput>
::PrintSelf(std::ostream& os, Indent indent) const
{
  this->Superclass::PrintSelf(os,indent);

  for(unsigned int i=0;i<itkGetStaticConstMacro(ImageDimension);i++)
    {
    os << indent << "Sigma["<< i << "] : " <<  m_Sigma[i] << std::endl;
    os << indent << "MaximumError["<< i << "] : " << m_MaximumError[i] << std::endl;
    os << indent << "Extent["<< i << "] : " << m_Extent[i] << std::endl;
    }
  os << indent << "MaximumKernelWidth: " << m_MaximumKernelWidth << std::endl;
  os << indent << "UseImageSpacing: " << m_UseImageSpacing << std::endl;

  os << indent << "Internal Image : " << m_InternalImage << std::endl;
  os << indent << "Image Caster : " << m_Caster << std::endl;

}

template <class TInputImage,class TOutput>
void
GaussianBlurImageFunction<TInputImage,TOutput>
::SetSigma(const double* sigma)
{
  unsigned int i;
  for (i=0; i<itkGetStaticConstMacro(ImageDimension); i++)
    {
    if ( sigma[i] != m_Sigma[i] )
      {
      break;
      }
    }
  if ( i < itkGetStaticConstMacro(ImageDimension) )
    {
    for (i=0; i<itkGetStaticConstMacro(ImageDimension); i++)
      {
      m_Sigma[i] = sigma[i];
      }
    this->RecomputeGaussianKernel();
    }
}


template <class TInputImage,class TOutput>
void
GaussianBlurImageFunction<TInputImage,TOutput>
::SetSigma( const double sigma)
{
  unsigned int i;
  for (i=0; i<itkGetStaticConstMacro(ImageDimension); i++)
    {
    if ( sigma != m_Sigma[i] )
      {
      break;
      }
    }
  if ( i < itkGetStaticConstMacro(ImageDimension) )
    {
    for (i=0; i<itkGetStaticConstMacro(ImageDimension); i++)
      {
      m_Sigma[i] = sigma;
      }
    this->RecomputeGaussianKernel();
    }
}

template <class TInputImage,class TOutput>
void
GaussianBlurImageFunction<TInputImage,TOutput>
::SetExtent(const double* extent)
{
  unsigned int i;
  for (i=0; i<itkGetStaticConstMacro(ImageDimension); i++)
    {
    if ( extent[i] != m_Extent[i] )
      {
      break;
      }
    }
  if ( i < itkGetStaticConstMacro(ImageDimension) )
    {
    for (i=0; i<itkGetStaticConstMacro(ImageDimension); i++)
      {
      m_Extent[i] = extent[i];
      }
    this->RecomputeGaussianKernel();
    }
}


template <class TInputImage,class TOutput>
void
GaussianBlurImageFunction<TInputImage,TOutput>
::SetExtent( const double extent)
{
  unsigned int i;
  for (i=0; i<itkGetStaticConstMacro(ImageDimension); i++)
    {
    if ( extent != m_Extent[i] )
      {
      break;
      }
    }
  if ( i < itkGetStaticConstMacro(ImageDimension) )
    {
    for (i=0; i<itkGetStaticConstMacro(ImageDimension); i++)
      {
      m_Extent[i] = extent;
      }
    this->RecomputeGaussianKernel();
    }
}

template <class TInputImage,class TOutput>
void
GaussianBlurImageFunction<TInputImage,TOutput>
::RecomputeGaussianKernel()
{

  typename InternalImageType::SizeType size;
  // Compute the convolution of each kernel in each direction
  for(unsigned int direction=0;direction<itkGetStaticConstMacro(ImageDimension);direction++)
    {
    GaussianOperatorType gaussianOperator;

    gaussianOperator.SetDirection(direction);
    gaussianOperator.SetMaximumError(m_MaximumError[direction]);
    gaussianOperator.SetMaximumKernelWidth(m_MaximumKernelWidth);

    if( (m_UseImageSpacing == true) && (this->GetInputImage()) )
      {
      if (this->GetInputImage()->GetSpacing()[direction] == 0.0)
        {
        itkExceptionMacro(<< "Pixel spacing cannot be zero");
        }
      else
        {
        gaussianOperator.SetVariance(m_Sigma[direction]*m_Sigma[direction]  / this->GetInputImage()->GetSpacing()[direction]);
        }
      }
    else
      {
      gaussianOperator.SetVariance(m_Sigma[direction]*m_Sigma[direction]);
      }

    gaussianOperator.CreateDirectional();
    m_OperatorArray[direction] = gaussianOperator;
    size[direction] = gaussianOperator.GetSize()[direction];
    }

  // Allocate the internal image
  m_InternalImage = InternalImageType::New();
  typename InternalImageType::RegionType region;
  region.SetSize(size);
  m_InternalImage->SetRegions(region);
  m_InternalImage->Allocate();
  m_InternalImage->FillBuffer(0);
}

template <class TInputImage,class TOutput>
TOutput
GaussianBlurImageFunction<TInputImage,TOutput>
::EvaluateAtIndex(const IndexType& index) const
{
  return this->EvaluateAtIndex( index, m_OperatorArray );
}

template <class TInputImage,class TOutput>
TOutput
GaussianBlurImageFunction<TInputImage,TOutput>
::EvaluateAtIndex(const IndexType& index, const OperatorArrayType & operatorArray ) const
{
  // First time we use the complete image and fill the internal image
  m_OperatorImageFunction->SetInputImage(m_Caster->GetOutput());
  m_OperatorImageFunction->SetOperator(operatorArray[0]);

  // if 1D Image we return the result
  if(itkGetStaticConstMacro(ImageDimension) == 1)
    {
    return m_OperatorImageFunction->EvaluateAtIndex(index);
    }

  // Compute the centered index of the neighborhood
  IndexType centerIndex;
  for(unsigned int i=0;i<itkGetStaticConstMacro(ImageDimension);i++)
    {
    centerIndex[i] = (unsigned long)((float)m_InternalImage->GetBufferedRegion().GetSize()[i]/2.0);
    }

  // first direction
  typename InternalImageType::IndexType ind;
  ind = index;

  //Define the region of the iterator
  typename InternalImageType::RegionType region;
  typename InternalImageType::SizeType size = m_InternalImage->GetBufferedRegion().GetSize();
  size[0]=1;
  region.SetSize(size);

  for(unsigned int i = 0;i<itkGetStaticConstMacro(ImageDimension);i++)
    {
    if(i != 0)
      {
      ind[i] -= centerIndex[i];
      }
    }
  region.SetIndex(ind);

  typename InternalImageType::RegionType regionN;
  regionN.SetSize(size);
  ind = centerIndex;
  for(unsigned int i = 0;i<itkGetStaticConstMacro(ImageDimension);i++)
    {
    if(i != 0)
      {
      ind[i] = 0;
      }
    }
  regionN.SetIndex(ind);

  typename InternalImageType::RegionType regionS = region;
  regionS.Crop( m_Caster->GetOutput()->GetBufferedRegion() );

  itk::ImageLinearConstIteratorWithIndex<InternalImageType> it(m_Caster->GetOutput(),regionS);
  itk::ImageLinearIteratorWithIndex<InternalImageType> itN(m_InternalImage,regionN);
  it.SetDirection(1);
  itN.SetDirection(1);
  it.GoToBeginOfLine();
  itN.GoToBeginOfLine();
  while( !it.IsAtEnd() )
    {
    while( !it.IsAtEndOfLine() )
      {
      itN.Set(m_OperatorImageFunction->EvaluateAtIndex(it.GetIndex()));
      ++it;
      ++itN;
      }
    it.NextLine();
    itN.NextLine();
    }

  // Do the convolution in other directions
  for(unsigned int direction=1;direction<itkGetStaticConstMacro(ImageDimension);direction++)
    {

    size[direction] = 1;
    ind = centerIndex;
    for(unsigned int i = 0;i<itkGetStaticConstMacro(ImageDimension);i++)
      {
      if(i > direction)
        {
        ind[i] = 0;
        }
      }
    region.SetSize(size);
    region.SetIndex(ind);


    m_OperatorImageFunction->SetInputImage(m_InternalImage);
    m_OperatorImageFunction->SetOperator(operatorArray[direction]);

    itk::ImageLinearIteratorWithIndex<InternalImageType> itr(m_InternalImage,region);

    unsigned int dir = direction +1;
    if(dir == itkGetStaticConstMacro(ImageDimension))
      {
      dir = itkGetStaticConstMacro(ImageDimension)-1;
      }

    itr.SetDirection(dir);
    itr.GoToBeginOfLine();
    while(!itr.IsAtEnd())
      {
      while(!itr.IsAtEndOfLine())
        {
        itr.Set(m_OperatorImageFunction->EvaluateAtIndex(itr.GetIndex()));
        ++itr;
        }
      itr.NextLine();
      }
    }

  return m_InternalImage->GetPixel(centerIndex);

}


template <class TInputImage,class TOutput>
void
GaussianBlurImageFunction<TInputImage,TOutput>
::RecomputeContinuousGaussianKernel(const double* offset) const
{
  for(unsigned int direction=0;direction<itkGetStaticConstMacro(ImageDimension);direction++)
    {
    NeighborhoodType gaussianNeighborhood;
    typename GaussianFunctionType::InputType pt;
    typename NeighborhoodType::SizeType size;
    size.Fill(0);
    size[direction] = (unsigned long)(m_Sigma[direction]*m_Extent[direction]);

    gaussianNeighborhood.SetRadius(size);

    typename NeighborhoodType::Iterator it = gaussianNeighborhood.Begin();

    itk::FixedArray<double,1> s;
    s[0]=m_Sigma[direction];
    m_GaussianFunction->SetSigma(s);

    unsigned int i=0;
    float sum = 0;
    while(it != gaussianNeighborhood.End() )
      {
      pt[0]= gaussianNeighborhood.GetOffset(i)[direction]-offset[direction];
      if( (m_UseImageSpacing == true) && (this->GetInputImage()) )
        {
        if (this->GetInputImage()->GetSpacing()[direction] == 0.0)
          {
          itkExceptionMacro(<< "Pixel spacing cannot be zero");
          }
        else
          {
          pt[0] *= this->GetInputImage()->GetSpacing()[direction];
          }
        }

      (*it)= m_GaussianFunction->Evaluate(pt);
      sum += (*it);
      i++;
      it++;
      }

    // Make the filter DC-Constant
    it = gaussianNeighborhood.Begin();
    while(it != gaussianNeighborhood.End() )
      {
      (*it) /= sum;
      it++;
      }
    m_ContinuousOperatorArray[direction] = gaussianNeighborhood;
    }
}

template <class TInputImage,class TOutput>
TOutput
GaussianBlurImageFunction<TInputImage,TOutput>
::Evaluate(const PointType& point) const
{
  ContinuousIndexType cindex;

  this->m_InternalImage->TransformPhysicalPointToContinuousIndex( point, cindex );

  return this->EvaluateAtContinuousIndex( cindex );
}

template <class TInputImage,class TOutput>
TOutput
GaussianBlurImageFunction<TInputImage,TOutput>
::EvaluateAtContinuousIndex( const ContinuousIndexType & cindex ) const
{
  IndexType index;

  index.CopyWithRound( cindex );

  double offset[itkGetStaticConstMacro(ImageDimension)];
  for(unsigned int i=0; i<itkGetStaticConstMacro(ImageDimension);i++)
    {
    offset[i] = cindex[i] - index[i];
    }

  this->RecomputeContinuousGaussianKernel( offset );

  return this->EvaluateAtIndex( index, m_ContinuousOperatorArray );
}

} // end namespace itk

#endif