1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170
|
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkGradientMagnitudeRecursiveGaussianImageFilter.h,v $
Language: C++
Date: $Date: 2007-09-27 11:36:40 $
Version: $Revision: 1.16 $
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 __itkGradientMagnitudeRecursiveGaussianImageFilter_h
#define __itkGradientMagnitudeRecursiveGaussianImageFilter_h
#include "itkNthElementImageAdaptor.h"
#include "itkImage.h"
#include "itkPixelTraits.h"
#include "itkRecursiveGaussianImageFilter.h"
#include "itkInPlaceImageFilter.h"
namespace itk
{
/** \class GradientMagnitudeRecursiveGaussianImageFilter
* \brief Computes the Magnitude of the Gradient of an image by convolution
* with the first derivative of a Gaussian.
*
* This filter is implemented using the recursive gaussian
* filters
*
*
* \ingroup GradientFilters
* \ingroup Singlethreaded
*/
// NOTE that the ITK_TYPENAME macro has to be used here in lieu
// of "typename" because VC++ doesn't like the typename keyword
// on the defaults of template parameters
template <typename TInputImage,
typename TOutputImage= TInputImage >
class ITK_EXPORT GradientMagnitudeRecursiveGaussianImageFilter:
public InPlaceImageFilter<TInputImage,TOutputImage>
{
public:
/** Standard class typedefs. */
typedef GradientMagnitudeRecursiveGaussianImageFilter Self;
typedef InPlaceImageFilter<TInputImage,TOutputImage> Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Pixel Type of the input image */
typedef TInputImage InputImageType;
typedef typename InputImageType::PixelType PixelType;
/** Image dimension. */
itkStaticConstMacro(ImageDimension, unsigned int,
TInputImage::ImageDimension);
typedef typename NumericTraits<PixelType>::RealType RealType;
/** Define the image type for internal computations
RealType is usually 'double' in NumericTraits.
Here we prefer float in order to save memory. */
typedef float InternalRealType;
typedef Image<InternalRealType,
itkGetStaticConstMacro(ImageDimension) > RealImageType;
/** Smoothing filter type */
typedef RecursiveGaussianImageFilter<
RealImageType,
RealImageType
> GaussianFilterType;
/** Derivative filter type, it will be the first in the pipeline */
typedef RecursiveGaussianImageFilter<
InputImageType,
RealImageType
> DerivativeFilterType;
/** Pointer to a gaussian filter. */
typedef typename GaussianFilterType::Pointer GaussianFilterPointer;
/** Pointer to a derivative filter. */
typedef typename DerivativeFilterType::Pointer DerivativeFilterPointer;
/** Pointer to the Output Image */
typedef typename TOutputImage::Pointer OutputImagePointer;
/** Type of the output Image */
typedef TOutputImage OutputImageType;
typedef typename OutputImageType::PixelType OutputPixelType;
/** Auxiliary image for holding the values of the squared gradient components */
typedef Image< InternalRealType,
itkGetStaticConstMacro(ImageDimension) > CumulativeImageType;
typedef typename CumulativeImageType::Pointer CumulativeImagePointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Runtime information support. */
itkTypeMacro(GradientMagnitudeRecursiveGaussianImageFilter,
InPlaceImageFilter);
/** Set Sigma value. Sigma is measured in the units of image spacing. */
void SetSigma( RealType sigma );
/** Define which normalization factor will be used for the Gaussian */
void SetNormalizeAcrossScale( bool normalizeInScaleSpace );
itkGetMacro( NormalizeAcrossScale, bool );
#ifdef ITK_USE_CONCEPT_CHECKING
/** Begin concept checking */
itkConceptMacro(InputHasNumericTraitsCheck,
(Concept::HasNumericTraits<PixelType>));
/** End concept checking */
#endif
protected:
GradientMagnitudeRecursiveGaussianImageFilter();
virtual ~GradientMagnitudeRecursiveGaussianImageFilter() {};
void PrintSelf(std::ostream& os, Indent indent) const;
/** Generate Data */
void GenerateData( void );
/** GradientMagnitudeRecursiveGaussianImageFilter needs all of the
* input to produce an output. Therefore,
* GradientMagnitudeRecursiveGaussianImageFilter needs to provide an
* implementation for GenerateInputRequestedRegion in order to
* inform the pipeline execution model. \sa
* ImageToImageFilter::GenerateInputRequestedRegion() */
virtual void GenerateInputRequestedRegion() throw(InvalidRequestedRegionError);
/** GradientMagnitudeRecursiveGaussianImageFilter produces all of
* the output. Therefore, it needs to provide an implementation of
* EnlargeOutputRequestedRegion(). */
void EnlargeOutputRequestedRegion(DataObject *output);
private:
GradientMagnitudeRecursiveGaussianImageFilter(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
GaussianFilterPointer m_SmoothingFilters[ImageDimension-1];
DerivativeFilterPointer m_DerivativeFilter;
/** Normalize the image across scale space */
bool m_NormalizeAcrossScale;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkGradientMagnitudeRecursiveGaussianImageFilter.txx"
#endif
#endif
|