| 1 |
|
/*========================================================================= |
| 2 |
|
|
| 3 |
|
Program: Insight Segmentation & Registration Toolkit |
| 4 |
|
Module: $RCSfile: itkCovarianceImageFunction.txx.html,v $ |
| 5 |
|
Language: C++ |
| 6 |
|
Date: $Date: 2006/01/17 19:15:34 $ |
| 7 |
|
Version: $Revision: 1.4 $ |
| 8 |
|
|
| 9 |
|
Copyright (c) Insight Software Consortium. All rights reserved. |
| 10 |
|
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details. |
| 11 |
|
|
| 12 |
|
This software is distributed WITHOUT ANY WARRANTY; without even |
| 13 |
|
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR |
| 14 |
|
PURPOSE. See the above copyright notices for more information. |
| 15 |
|
|
| 16 |
|
=========================================================================*/ |
| 17 |
DEF |
#ifndef _itkCovarianceImageFunction_txx |
| 18 |
DEF |
#define _itkCovarianceImageFunction_txx |
| 19 |
|
#include "itkCovarianceImageFunction.h" |
| 20 |
|
#include "itkMatrix.h" |
| 21 |
|
#include "itkNumericTraits.h" |
| 22 |
|
#include "itkConstNeighborhoodIterator.h" |
| 23 |
|
|
| 24 |
|
namespace itk |
| 25 |
|
{ |
| 26 |
|
|
| 27 |
|
/** |
| 28 |
IND |
**** Constructor |
| 29 |
IND |
****/ |
| 30 |
|
template <class TInputImage, class TCoordRep> |
| 31 |
|
CovarianceImageFunction<TInputImage,TCoordRep> |
| 32 |
|
::CovarianceImageFunction() |
| 33 |
|
{ |
| 34 |
|
m_NeighborhoodRadius = 1; |
| 35 |
|
} |
| 36 |
|
|
| 37 |
|
|
| 38 |
|
/** |
| 39 |
IND |
**** |
| 40 |
IND |
****/ |
| 41 |
|
template <class TInputImage, class TCoordRep> |
| 42 |
|
void |
| 43 |
|
CovarianceImageFunction<TInputImage,TCoordRep> |
| 44 |
|
::PrintSelf(std::ostream& os, Indent indent) const |
| 45 |
|
{ |
| 46 |
|
this->Superclass::PrintSelf(os,indent); |
| 47 |
|
os << indent << "NeighborhoodRadius: " << m_NeighborhoodRadius << std::endl; |
| 48 |
|
} |
| 49 |
|
|
| 50 |
|
|
| 51 |
|
/** |
| 52 |
|
* |
| 53 |
|
*/ |
| 54 |
|
template <class TInputImage, class TCoordRep> |
| 55 |
|
typename CovarianceImageFunction<TInputImage,TCoordRep> |
| 56 |
|
::RealType |
| 57 |
|
CovarianceImageFunction<TInputImage,TCoordRep> |
| 58 |
|
::EvaluateAtIndex(const IndexType& index) const |
| 59 |
|
{ |
| 60 |
|
typedef typename TInputImage::PixelType PixelType; |
| 61 |
|
typedef typename PixelType::ValueType PixelComponentType; |
| 62 |
|
|
| 63 |
LEN |
typedef typename NumericTraits< PixelComponentType >::RealType PixelComponentRealType; |
| 64 |
|
|
| 65 |
|
const unsigned int VectorDimension = |
| 66 |
IND |
******::itk::GetVectorDimension< PixelType >::VectorDimension; |
| 67 |
|
|
| 68 |
|
RealType covariance = RealType( VectorDimension, VectorDimension ); |
| 69 |
|
|
| 70 |
|
|
| 71 |
|
|
| 72 |
|
if( !this->GetInputImage() ) |
| 73 |
|
{ |
| 74 |
|
itkExceptionMacro( << "No image connected to CovarianceImageFunction"); |
| 75 |
|
covariance.fill( NumericTraits< PixelComponentRealType >::max() ); |
| 76 |
|
return covariance; |
| 77 |
|
} |
| 78 |
|
|
| 79 |
|
if ( !this->IsInsideBuffer( index ) ) |
| 80 |
|
{ |
| 81 |
|
covariance.fill( NumericTraits< PixelComponentRealType >::max() ); |
| 82 |
|
return covariance; |
| 83 |
|
} |
| 84 |
|
|
| 85 |
|
covariance.fill( NumericTraits< PixelComponentRealType >::Zero ); |
| 86 |
|
|
| 87 |
|
|
| 88 |
|
typedef vnl_vector< PixelComponentRealType > MeanVectorType; |
| 89 |
|
MeanVectorType mean = MeanVectorType( VectorDimension ); |
| 90 |
|
mean.fill( NumericTraits< PixelComponentRealType >::Zero ); |
| 91 |
|
|
| 92 |
|
// Create an N-d neighborhood kernel, using a zeroflux boundary condition |
| 93 |
|
typename InputImageType::SizeType kernelSize; |
| 94 |
|
kernelSize.Fill( m_NeighborhoodRadius ); |
| 95 |
|
|
| 96 |
|
ConstNeighborhoodIterator<InputImageType> |
| 97 |
LEN,IND |
****it(kernelSize, this->GetInputImage(), this->GetInputImage()->GetBufferedRegion()); |
| 98 |
|
|
| 99 |
|
// Set the iterator at the desired location |
| 100 |
|
it.SetLocation(index); |
| 101 |
|
|
| 102 |
|
// Walk the neighborhood |
| 103 |
|
const unsigned int size = it.Size(); |
| 104 |
|
for (unsigned int i = 0; i < size; ++i) |
| 105 |
|
{ |
| 106 |
|
const PixelType pixel = it.GetPixel(i); |
| 107 |
|
|
| 108 |
|
for(unsigned int dimx=0; dimx<VectorDimension; dimx++) |
| 109 |
|
{ |
| 110 |
|
mean[ dimx ] += pixel[ dimx ]; |
| 111 |
|
for(unsigned int dimy=0; dimy<VectorDimension; dimy++) |
| 112 |
|
{ |
| 113 |
|
covariance[dimx][dimy] += |
| 114 |
|
static_cast<PixelComponentRealType>( pixel[dimx] ) * |
| 115 |
IND |
************static_cast<PixelComponentRealType>( pixel[dimy] ); |
| 116 |
|
} |
| 117 |
|
} |
| 118 |
|
} |
| 119 |
|
|
| 120 |
|
const PixelComponentRealType rsize = |
| 121 |
IND |
**********static_cast< PixelComponentRealType >( size ); |
| 122 |
|
|
| 123 |
|
mean /= rsize; |
| 124 |
|
|
| 125 |
|
for(unsigned int dimx=0; dimx<VectorDimension; dimx++) |
| 126 |
|
{ |
| 127 |
|
for(unsigned int dimy=0; dimy<VectorDimension; dimy++) |
| 128 |
|
{ |
| 129 |
|
covariance[dimx][dimy] /= rsize; |
| 130 |
|
covariance[dimx][dimy] -= mean[dimx] * mean[dimy]; |
| 131 |
|
} |
| 132 |
|
} |
| 133 |
|
|
| 134 |
|
return ( covariance ); |
| 135 |
|
} |
| 136 |
|
|
| 137 |
|
|
| 138 |
|
} // namespace itk |
| 139 |
|
|
| 140 |
|
#endif |
| 141 |
|
|
