medianresampler_d.h

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#ifndef AIMS_RESAMPLING_MEDIANRESAMPLER_D_H
#define AIMS_RESAMPLING_MEDIANRESAMPLER_D_H
 
#include <aims/resampling/majoritylabelresampler.h>
 
#include <cartobase/type/converter.h>
 
#include <cmath>
 
namespace aims
{
 
template < class T >
MedianResampler< T >::MedianResampler()
  : SplineResampler< T >()
{
}
 
 
template < class T >
MedianResampler< T >::~MedianResampler()
{
}
 
 
template < class T >
int MedianResampler< T >::getOrder() const
{
 
  return 201;
 
}
 
 
template < class T >
void MedianResampler< T >::
doResampleChannel( const carto::Volume< ChannelType >& inVolume,
                   const soma::Transformation3d& invTransform3d,
                   const ChannelType& outBackground,
                   const Point3df& outLocation,
                   ChannelType& outValue, int t ) const
{
 
  const ChannelType *i = &inVolume.at( 0, 0, 0, t );
  const ChannelType *pi, *pj;
 
  Point3df normalizedInLocation;
  normalizedInLocation = invTransform3d.transform( outLocation );
 
  float xf = round(normalizedInLocation[0]);
  float yf = round(normalizedInLocation[1]);
  float zf = round(normalizedInLocation[2]);
 
  std::vector<int> dims = inVolume.getSize();
  int dimx = dims[0], dimy = dims[1], dimz = dims[2];
 
  // The test is done using floating-point so that NaN values are excluded (the
  // background value is returned if the transformation yields NaN)
  if ( ( xf >= 0 ) && ( xf < dimx ) &&
       ( yf >= 0 ) && ( yf < dimy ) &&
       ( zf >= 0 ) && ( zf < dimz ) )
  {
 
    double weightX0, weightY0, weightX1, weightY1;
    long foldX0, foldY0, foldX1, foldY1;
    double intensity, qi, qj;
 
    // first y contribution
    int y = static_cast<long>(floor(normalizedInLocation[1]));
    weightY0 = getBSplineWeight( y, normalizedInLocation[1] );
    foldY0 = (long)this->getFold( y, dims[1] ) * dims[0];
 
    // second y contribution
    ++ y;
    weightY1 = getBSplineWeight( y, normalizedInLocation[1] );
    foldY1 = (long)this->getFold( y, dimy ) * dimx;
 
    // first x contribution
    int x = static_cast<long>(floor(normalizedInLocation[0]));
    weightX0 = getBSplineWeight( x, normalizedInLocation[0] );
    foldX0 = (long)this->getFold( x, dimx );
 
    // second x contribution
    ++ x;
    weightX1 = getBSplineWeight( x, normalizedInLocation[0] );
    foldX1 = (long)this->getFold( x, dimx );
 
    std::map<ChannelType, unsigned long> values;
    unsigned long nv = 0;
 
    if ( dimz == 1 )
    {
 
      //counting contributions
      pj = i;
      pi = pj + (size_t)(foldY0);
      if( weightY0 != 0 )
      {
        if( weightX0 != 0 )
        {
          values[*( pi + (size_t)(foldX0) )]++;
          ++nv;
        }
        if( weightX1 != 0 )
        {
          values[*( pi + size_t(foldX1) )]++;
          ++nv;
        }
      }
      if( weightY1 != 0 )
      {
        pi = pj + foldY1;
        if( weightX0 != 0 && weightY1 != 0 )
        {
          values[*( pi + (size_t)(foldX0) )]++;
          ++nv;
        }
        if( weightX1 != 0 && weightY1 != 0 )
        {
          values[*( pi + (size_t)(foldX1) )]++;
          ++nv;
        }
      }
 
    }
    else
    {
 
      // first z contribution
      int z = static_cast<long>(floor(normalizedInLocation[2]));
      if( getBSplineWeight( z, normalizedInLocation[2] ) != 0 )
      {
        pj = i + (size_t)(this->getFold( z, dimz )) * dimx * dimy;
        pi = pj + (size_t)(foldY0);
 
        if( weightY0 != 0 )
        {
          if( weightX0 != 0 )
          {
            values[*( pi + (size_t)(foldX0) )]++;
            ++nv;
          }
          if( weightX1 != 0 )
          {
            values[*( pi + size_t(foldX1) )]++;
            ++nv;
          }
        }
        if( weightY1 != 0 )
        {
          pi = pj + foldY1;
          if( weightX0 != 0 && weightY1 != 0 )
          {
            values[*( pi + (size_t)(foldX0) )]++;
            ++nv;
          }
          if( weightX1 != 0 && weightY1 != 0 )
          {
            values[*( pi + (size_t)(foldX1) )]++;
            ++nv;
          }
        }
 
      }
      // second z contribution
      ++ z;
      if( getBSplineWeight( z, normalizedInLocation[2] ) != 0 )
      {
        pj = i + (size_t)(this->getFold( z, dimz )) * dimx *
            dimy;
        pi = pj + (size_t)(foldY0);
 
        if( weightY0 != 0 )
        {
          if( weightX0 != 0 )
          {
            values[*( pi + (size_t)(foldX0) )]++;
            ++nv;
          }
          if( weightX1 != 0 )
          {
            values[*( pi + size_t(foldX1) )]++;
            ++nv;
          }
        }
        if( weightY1 != 0 )
        {
          pi = pj + foldY1;
          if( weightX0 != 0 && weightY1 != 0 )
          {
            values[*( pi + (size_t)(foldX0) )]++;
            ++nv;
          }
          if( weightX1 != 0 && weightY1 != 0 )
          {
            values[*( pi + (size_t)(foldX1) )]++;
            ++nv;
          }
        }
      }
    }
 
    unsigned long c = 0, nv2 = (unsigned long) ::ceil( nv / 2. );
    ChannelType medv = 0;
    typename std::map<ChannelType, unsigned long>::const_iterator
      iv, ev = values.end();
 
    for( iv=values.begin(); iv!=ev; ++iv )
    {
      c += iv->second;
      medv = iv->first;
      if( c >= nv2 )
        break;
    }
    if( c != 0 )
      intensity = medv;
    else
      intensity = outBackground;
 
    carto::RawConverter<double, ChannelType>().convert(intensity, outValue);
 
  }
  else
  {
 
    outValue = outBackground;
 
  }
 
}
 
template < class T >
double MedianResampler< T >::getBSplineWeight( int i, double x ) const
{
 
  x = fabs( x - ( double )i );
  return ( x > 1.0 ) ? 0.0 : 1.0 - x;
 
}
 
} // namespace aims
 
#endif