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
|
/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkParametricBlindLeastSquaresDeconvolutionImageFilter_h
#define itkParametricBlindLeastSquaresDeconvolutionImageFilter_h
#include "itkIterativeDeconvolutionImageFilter.h"
#include "itkParametricImageSource.h"
#include "itkTernaryGeneratorImageFilter.h"
namespace itk
{
/**
* \class ParametricBlindLeastSquaresDeconvolutionImageFilter
*
* \brief Least-squares blind deconvolution filter that also estimates
* the parameters of a user-supplied parametric point-spread function.
*
* This filter takes a parametric kernel image source instead of a
* static kernel image. During the deconvolution iterations, a new
* estimate of the restored image is produced, along with a new
* estimate of the kernel parameters. The parameters are available
* through the kernel image sources GetParameters() method after the
* filter has executed.
*
* Both the image estimate and the kernel parameter estimate are
* produced through gradient descent on a sum-of-squared differences
* objective function, making this method suitable for zero-mean
* Gaussian white noise.
*
* This filter produces output in two forms: a deconvolved image and the
* parameters of the input kernel image source.
*
* \warning The method SetKernelImage(), inherited from the superclass
* of this filter, is publicly available. However, this algorithm does
* not use the static kernel image set through this method. Instead,
* it uses the output of the parametric kernel source you specify.
*
* \author Cory Quammen, The University of North Carolina at Chapel Hill
*
* \ingroup ITKDeconvolution
*/
template <typename TInputImage, typename TKernelSource, typename TOutputImage = TInputImage>
class ITK_TEMPLATE_EXPORT ParametricBlindLeastSquaresDeconvolutionImageFilter
: public IterativeDeconvolutionImageFilter<TInputImage, typename TKernelSource::OutputImageType, TOutputImage>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(ParametricBlindLeastSquaresDeconvolutionImageFilter);
/** Standard type alias. */
using Self = ParametricBlindLeastSquaresDeconvolutionImageFilter;
using Superclass =
IterativeDeconvolutionImageFilter<TInputImage, typename TKernelSource::OutputImageType, TOutputImage>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** Other useful type alias. */
using InputImageType = TInputImage;
using OutputImageType = TOutputImage;
/** Internal types used by the FFT filters. */
using typename Superclass::InternalImageType;
using typename Superclass::InternalImagePointerType;
using typename Superclass::InternalComplexType;
using typename Superclass::InternalComplexImageType;
using typename Superclass::InternalComplexImagePointerType;
/** Type for the parametric kernel source. */
using KernelSourceType = TKernelSource;
using KernelSourcePointer = typename KernelSourceType::Pointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(ParametricBlindLeastSquaresDeconvolutionImageFilter);
/** Set/get the parametric kernel source. */
void
SetKernelSource(KernelSourceType * kernelSource);
itkGetModifiableObjectMacro(KernelSource, KernelSourceType);
/** Set/get the scale factor (also known as learning rate) for the
* image intensity gradient descent. */
itkSetMacro(Alpha, double);
itkGetMacro(Alpha, double);
/** Set/get the scale factor (also known as learning rate) for the
* parameter gradient descent. */
itkSetMacro(Beta, double);
itkGetMacro(Beta, double);
protected:
ParametricBlindLeastSquaresDeconvolutionImageFilter();
~ParametricBlindLeastSquaresDeconvolutionImageFilter() override = default;
void
Initialize(ProgressAccumulator * progress, float progressWeight, float iterationProgressWeight) override;
void
Iteration(ProgressAccumulator * progress, float iterationProgressWeight) override;
void
Finish(ProgressAccumulator * progress, float progressWeight) override;
void
PrintSelf(std::ostream & os, Indent indent) const override;
private:
KernelSourcePointer m_KernelSource{};
/** Step sizes for the gradient descent of the image and the
* kernel parameters. These are very different spaces, so they
* deserve different step size parameters. */
double m_Alpha{};
double m_Beta{};
/** Temporary images. */
InternalComplexImagePointerType m_TransformedInput{};
InternalComplexImagePointerType m_TransformedCurrentEstimate{};
/** These are the internal filters that perform the updating of the
* image estimate. */
using DifferenceFilterType = TernaryGeneratorImageFilter<InternalComplexImageType,
InternalComplexImageType,
InternalComplexImageType,
InternalComplexImageType>;
typename DifferenceFilterType::Pointer m_DifferenceFilter{};
using ImageUpdateFilterType = TernaryGeneratorImageFilter<InternalComplexImageType,
InternalComplexImageType,
InternalComplexImageType,
InternalComplexImageType>;
typename ImageUpdateFilterType::Pointer m_ImageUpdateFilter{};
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkParametricBlindLeastSquaresDeconvolutionImageFilter.hxx"
#endif
#endif
|
