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
|
/*=========================================================================
*
* 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 "itkRandomImageSource.h"
#include "itkBinaryThresholdImageFilter.h"
#include "itkBinaryMedianImageFilter.h"
#include "itkTextOutput.h"
#include "itkTestingMacros.h"
int
itkBinaryMedianImageFilterTest(int, char *[])
{
// Comment the following if you want to use the itk text output window
itk::OutputWindow::SetInstance(itk::TextOutput::New());
using ImageType = itk::Image<unsigned short, 2>;
itk::RandomImageSource<ImageType>::Pointer random;
random = itk::RandomImageSource<ImageType>::New();
random->SetMin(0);
random->SetMax(100);
ImageType::SizeValueType randomSize[2];
randomSize[0] = randomSize[1] = 8;
random->SetSize(randomSize);
ImageType::SpacingValueType spacing[2] = { 0.7, 2.1 };
random->SetSpacing(spacing);
ImageType::PointValueType origin[2] = { 15, 400 };
random->SetOrigin(origin);
ImageType::PixelType foreground = 97; // prime numbers are good testers
ImageType::PixelType background = 29;
itk::BinaryThresholdImageFilter<ImageType, ImageType>::Pointer thresholder;
thresholder = itk::BinaryThresholdImageFilter<ImageType, ImageType>::New();
thresholder->SetInput(random->GetOutput());
thresholder->SetLowerThreshold(30);
thresholder->SetUpperThreshold(100);
thresholder->SetInsideValue(foreground);
thresholder->SetOutsideValue(background);
// Create a median image
itk::BinaryMedianImageFilter<ImageType, ImageType>::Pointer median;
median = itk::BinaryMedianImageFilter<ImageType, ImageType>::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(median, BinaryMedianImageFilter, ImageToImageFilter);
median->SetInput(thresholder->GetOutput());
median->SetForegroundValue(foreground);
ITK_TEST_SET_GET_VALUE(foreground, median->GetForegroundValue());
median->SetBackgroundValue(background);
ITK_TEST_SET_GET_VALUE(background, median->GetBackgroundValue());
// define the neighborhood size used for the median filter (5x5)
ImageType::SizeType neighRadius;
neighRadius[0] = 1;
neighRadius[1] = 1;
median->SetRadius(neighRadius);
ITK_TEST_SET_GET_VALUE(neighRadius, median->GetRadius());
// run the algorithm
median->Update();
itk::ImageRegionIterator<ImageType> it;
it = itk::ImageRegionIterator<ImageType>(random->GetOutput(), random->GetOutput()->GetBufferedRegion());
std::cout << "Input image" << std::endl;
unsigned int i;
for (i = 1; !it.IsAtEnd(); ++i, ++it)
{
std::cout << '\t' << it.Get();
if ((i % 8) == 0)
{
std::cout << std::endl;
}
}
it = itk::ImageRegionIterator<ImageType>(thresholder->GetOutput(), thresholder->GetOutput()->GetBufferedRegion());
std::cout << "Binary image" << std::endl;
for (i = 1; !it.IsAtEnd(); ++i, ++it)
{
std::cout << '\t' << it.Get();
if ((i % 8) == 0)
{
std::cout << std::endl;
}
}
std::cout << "Output image" << std::endl;
it = itk::ImageRegionIterator<ImageType>(median->GetOutput(), median->GetOutput()->GetBufferedRegion());
for (i = 1; !it.IsAtEnd(); ++i, ++it)
{
std::cout << '\t' << it.Get();
if ((i % 8) == 0)
{
std::cout << std::endl;
}
}
return EXIT_SUCCESS;
}
|
