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
|
/*=========================================================================
*
* 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.
*
*=========================================================================*/
#include <iostream>
#include "itkAffineTransform.h"
#include "itkResampleImageFilter.h"
#include "itkImageFileWriter.h"
#include "itkMath.h"
#include "itkTestingMacros.h"
int
itkResampleImageTest(int, char *[])
{
constexpr unsigned int VDimension = 2;
using PixelType = float;
using ImageType = itk::Image<PixelType, VDimension>;
using ImageIndexType = ImageType::IndexType;
using ImagePointerType = ImageType::Pointer;
using ImageRegionType = ImageType::RegionType;
using ImageSizeType = ImageType::SizeType;
using CoordRepType = double;
using AffineTransformType = itk::AffineTransform<CoordRepType, VDimension>;
using InterpolatorType = itk::LinearInterpolateImageFunction<ImageType, CoordRepType>;
// Create and configure an image
ImagePointerType image = ImageType::New();
ImageIndexType index = { { 0, 0 } };
ImageSizeType size = { { 18, 12 } };
ImageRegionType region{ index, size };
image->SetLargestPossibleRegion(region);
image->SetBufferedRegion(region);
image->Allocate();
// Fill image with a ramp
itk::ImageRegionIteratorWithIndex<ImageType> iter(image, region);
PixelType value;
for (iter.GoToBegin(); !iter.IsAtEnd(); ++iter)
{
index = iter.GetIndex();
value = index[0] + index[1];
iter.Set(value);
}
// Create an affine transformation
auto aff = AffineTransformType::New();
aff->Scale(0.5);
// Create a linear interpolation image function
auto interp = InterpolatorType::New();
interp->SetInputImage(image);
// Create and configure a resampling filter
itk::ResampleImageFilter<ImageType, ImageType>::Pointer resample =
itk::ResampleImageFilter<ImageType, ImageType>::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(resample, ResampleImageFilter, ImageToImageFilter);
resample->SetInput(image);
ITK_TEST_SET_GET_VALUE(image, resample->GetInput());
resample->SetSize(size);
ITK_TEST_SET_GET_VALUE(size, resample->GetSize());
resample->SetTransform(aff);
ITK_TEST_SET_GET_VALUE(aff, resample->GetTransform());
resample->SetInterpolator(interp);
ITK_TEST_SET_GET_VALUE(interp, resample->GetInterpolator());
index.Fill(0);
resample->SetOutputStartIndex(index);
ITK_TEST_SET_GET_VALUE(index, resample->GetOutputStartIndex());
ImageType::PointType origin;
origin.Fill(0.0);
resample->SetOutputOrigin(origin);
ITK_TEST_SET_GET_VALUE(origin, resample->GetOutputOrigin());
ImageType::SpacingType spacing;
spacing.Fill(1.0);
resample->SetOutputSpacing(spacing);
ITK_TEST_SET_GET_VALUE(spacing, resample->GetOutputSpacing());
// Run the resampling filter
resample->Update();
// Check if desired results were obtained
bool passed = true;
ImageType::RegionType region2;
region2 = resample->GetOutput()->GetRequestedRegion();
itk::ImageRegionIteratorWithIndex<ImageType> iter2(resample->GetOutput(), region2);
PixelType pixval;
const double tolerance = 1e-30;
for (iter2.GoToBegin(); !iter2.IsAtEnd(); ++iter2)
{
index = iter2.GetIndex();
value = iter2.Get();
pixval = value;
auto expectedValue = static_cast<PixelType>((index[0] + index[1]) / 2.0);
if (!itk::Math::FloatAlmostEqual(expectedValue, pixval, 10, tolerance))
{
std::cout << "Error in resampled image: Pixel " << index << "value = " << value << " "
<< "pixval = " << pixval << " "
<< "expected = " << expectedValue << std::endl;
passed = false;
}
}
// Report success or failure
if (!passed)
{
std::cout << "Resampling test failed" << std::endl;
return EXIT_FAILURE;
}
// Exercise error handling
try
{
std::cout << "Setting interpolator to nullptr" << std::endl;
passed = false;
resample->SetInterpolator(nullptr);
resample->Update();
}
catch (const itk::ExceptionObject & err)
{
std::cout << err << std::endl;
passed = true;
resample->ResetPipeline();
resample->SetInterpolator(interp);
}
if (!passed)
{
std::cout << "Resampling test failed" << std::endl;
return EXIT_FAILURE;
}
std::cout << "Test passed." << std::endl;
return EXIT_SUCCESS;
}
|
