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
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
|
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkGradientRecursiveGaussianImageFilter.h
Language: C++
Date: $Date$
Version: $Revision$
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 __itkGradientRecursiveGaussianImageFilter_h
#define __itkGradientRecursiveGaussianImageFilter_h
#include "itkRecursiveGaussianImageFilter.h"
#include "itkNthElementImageAdaptor.h"
#include "itkImage.h"
#include "itkCovariantVector.h"
#include "itkPixelTraits.h"
#include "itkProgressAccumulator.h"
#include <vector>
namespace itk
{
/** \class GradientRecursiveGaussianImageFilter
* \brief Computes 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= Image< CovariantVector<
ITK_TYPENAME NumericTraits< ITK_TYPENAME TInputImage::PixelType>::RealType,
::itk::GetImageDimension<TInputImage>::ImageDimension >,
::itk::GetImageDimension<TInputImage>::ImageDimension > >
class ITK_EXPORT GradientRecursiveGaussianImageFilter:
public ImageToImageFilter<TInputImage,TOutputImage>
{
public:
/** Standard class typedefs. */
typedef GradientRecursiveGaussianImageFilter Self;
typedef ImageToImageFilter<TInputImage,TOutputImage> Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Pixel Type of the input image */
typedef TInputImage InputImageType;
typedef typename TInputImage::PixelType PixelType;
typedef typename NumericTraits<PixelType>::RealType RealType;
/** Image dimension. */
itkStaticConstMacro(ImageDimension, unsigned int,
TInputImage::ImageDimension);
/** 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;
/** Output Image Nth Element Adaptor
* This adaptor allows to use conventional scalar
* smoothing filters to compute each one of the
* components of the gradient image pixels. */
typedef NthElementImageAdaptor< TOutputImage,
InternalRealType > OutputImageAdaptorType;
typedef typename OutputImageAdaptorType::Pointer OutputImageAdaptorPointer;
/** 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;
typedef typename PixelTraits<OutputPixelType>::ValueType OutputComponentType;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Runtime information support. */
itkTypeMacro(GradientRecursiveGaussianImageFilter,
ImageToImageFilter);
/** 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 );
itkGetConstMacro( NormalizeAcrossScale, bool );
/** GradientRecursiveGaussianImageFilter needs all of the input to produce an
* output. Therefore, GradientRecursiveGaussianImageFilter needs to provide
* an implementation for GenerateInputRequestedRegion in order to inform
* the pipeline execution model.
* \sa ImageToImageFilter::GenerateInputRequestedRegion() */
virtual void GenerateInputRequestedRegion() throw(InvalidRequestedRegionError);
/** The UseImageDirection flag determines whether the gradients are
* computed with respect to the image grid or with respect to the physical
* space. When this flag is ON the gradients are computed with respect to
* the coodinate system of physical space. The difference is whether we take
* into account the image Direction or not. The flag ON will take into
* account the image direction and will result in an extra matrix
* multiplication compared to the amount of computation performed when the
* flag is OFF.
* The default value of this flag is the same as the CMAKE option
* ITK_IMAGE_BEHAVES_AS_ORIENTED_IMAGE (i.e ON by default when ITK_IMAGE_BEHAVES_AS_ORIENTED_IMAGE is ON,
* and OFF by default when ITK_IMAGE_BEHAVES_AS_ORIENTED_IMAGE is
* OFF). */
itkSetMacro( UseImageDirection, bool );
itkGetConstMacro( UseImageDirection, bool );
itkBooleanMacro( UseImageDirection );
#ifdef ITK_USE_CONCEPT_CHECKING
/** Begin concept checking */
itkConceptMacro(InputHasNumericTraitsCheck,
(Concept::HasNumericTraits<PixelType>));
itkConceptMacro(OutputHasPixelTraitsCheck,
(Concept::HasPixelTraits<OutputPixelType>));
/** End concept checking */
#endif
protected:
GradientRecursiveGaussianImageFilter();
virtual ~GradientRecursiveGaussianImageFilter() {};
void PrintSelf(std::ostream& os, Indent indent) const;
/** Generate Data */
void GenerateData( void );
// Override since the filter produces the entire dataset
void EnlargeOutputRequestedRegion(DataObject *output);
private:
GradientRecursiveGaussianImageFilter(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
std::vector<GaussianFilterPointer> m_SmoothingFilters;
DerivativeFilterPointer m_DerivativeFilter;
OutputImageAdaptorPointer m_ImageAdaptor;
/** Normalize the image across scale space */
bool m_NormalizeAcrossScale;
/** Take into account image orientation when computing the Gradient */
bool m_UseImageDirection;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkGradientRecursiveGaussianImageFilter.txx"
#endif
#endif
|
