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
196
197
198
199
200
201
202
203
204
205
206
207
|
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: MedianImageFilter.cxx
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.
=========================================================================*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif
#ifdef __BORLANDC__
#define ITK_LEAN_AND_MEAN
#endif
// Software Guide : BeginCommandLineArgs
// INPUTS: {BrainProtonDensitySlice.png}
// OUTPUTS: {MedianImageFilterOutput.png}
// Software Guide : EndCommandLineArgs
// Software Guide : BeginLatex
//
// The \doxygen{MedianImageFilter} is commonly used as a robust approach for
// noise reduction. This filter is particularly efficient against
// \emph{salt-and-pepper} noise. In other words, it is robust to the presence
// of gray-level outliers. MedianImageFilter computes the value of each output
// pixel as the statistical median of the neighborhood of values around the
// corresponding input pixel. The following figure illustrates the local
// effect of this filter in a $2D$ case. The statistical median of the
// neighborhood on the left is passed as the output value associated with the
// pixel at the center of the neighborhood.
//
//
// \begin{center}
// \begin{picture}(200,46)
// \put( 5.0, 0.0 ){\framebox(30.0,15.0){25}}
// \put( 35.0, 0.0 ){\framebox(30.0,15.0){30}}
// \put( 65.0, 0.0 ){\framebox(30.0,15.0){32}}
// \put( 5.0, 15.0 ){\framebox(30.0,15.0){27}}
// \put( 35.0, 15.0 ){\framebox(30.0,15.0){25}}
// \put( 65.0, 15.0 ){\framebox(30.0,15.0){29}}
// \put( 5.0, 30.0 ){\framebox(30.0,15.0){28}}
// \put( 35.0, 30.0 ){\framebox(30.0,15.0){26}}
// \put( 65.0, 30.0 ){\framebox(30.0,15.0){50}}
// \put( 100.0, 22.0 ){\vector(1,0){20.0}}
// \put( 125.0, 15.0 ){\framebox(30.0,15.0){28}}
// \end{picture}
// \end{center}
//
//
// This filter will work on images of any dimension thanks to the internal
// use of \doxygen{NeighborhoodIterator} and
// \doxygen{NeighborhoodOperator}. The size of the neighborhood over which
// the median is computed can be set by the user.
//
// \index{itk::MedianImageFilter}
//
// Software Guide : EndLatex
#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
// Software Guide : BeginLatex
//
// The header file corresponding to this filter should be included first.
//
// \index{itk::MedianImageFilter!header}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkMedianImageFilter.h"
// Software Guide : EndCodeSnippet
int main( int argc, char * argv[] )
{
if( argc < 3 )
{
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputImageFile outputImageFile" << std::endl;
return EXIT_FAILURE;
}
// Software Guide : BeginLatex
//
// Then the pixel and image types of the input and output must be defined.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef unsigned char InputPixelType;
typedef unsigned char OutputPixelType;
typedef itk::Image< InputPixelType, 2 > InputImageType;
typedef itk::Image< OutputPixelType, 2 > OutputImageType;
// Software Guide : EndCodeSnippet
typedef itk::ImageFileReader< InputImageType > ReaderType;
typedef itk::ImageFileWriter< OutputImageType > WriterType;
ReaderType::Pointer reader = ReaderType::New();
WriterType::Pointer writer = WriterType::New();
reader->SetFileName( argv[1] );
writer->SetFileName( argv[2] );
// Software Guide : BeginLatex
//
// Using the image types, it is now possible to define the filter type
// and create the filter object.
//
// \index{itk::MedianImageFilter!instantiation}
// \index{itk::MedianImageFilter!New()}
// \index{itk::MedianImageFilter!Pointer}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::MedianImageFilter<
InputImageType, OutputImageType > FilterType;
FilterType::Pointer filter = FilterType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The size of the neighborhood is defined along every dimension by
// passing a \code{SizeType} object with the corresponding values. The
// value on each dimension is used as the semi-size of a rectangular
// box. For example, in $2D$ a size of \(1,2\) will result in a $3 \times
// 5$ neighborhood.
//
// \index{itk::MedianImageFilter!Radius}
// \index{itk::MedianImageFilter!Neighborhood}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
InputImageType::SizeType indexRadius;
indexRadius[0] = 1; // radius along x
indexRadius[1] = 1; // radius along y
filter->SetRadius( indexRadius );
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The input to the filter can be taken from any other filter, for example
// a reader. The output can be passed down the pipeline to other filters,
// for example, a writer. An update call on any downstream filter will
// trigger the execution of the median filter.
//
// \index{itk::MedianImageFilter!SetInput()}
// \index{itk::MedianImageFilter!GetOutput()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
filter->SetInput( reader->GetOutput() );
writer->SetInput( filter->GetOutput() );
writer->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// \begin{figure}
// \center
// \includegraphics[width=0.44\textwidth]{BrainProtonDensitySlice.eps}
// \includegraphics[width=0.44\textwidth]{MedianImageFilterOutput.eps}
// \itkcaption[Effect of the Median filter.]{Effect of the MedianImageFilter on a
// slice from a MRI proton density brain image.}
// \label{fig:MedianImageFilterOutput}
// \end{figure}
//
// Figure \ref{fig:MedianImageFilterOutput} illustrates the effect of the MedianImageFilter
// filter on a slice of MRI brain image using a neighborhood radius of
// \(1,1\), which corresponds to a $ 3 \times 3 $ classical neighborhood.
// The filtered image demonstrates the moderate tendency of the median
// filter to preserve edges.
//
// Software Guide : EndLatex
return EXIT_SUCCESS;
}
|
