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
|
/*
* Copyright (C) 2005-2020 Centre National d'Etudes Spatiales (CNES)
*
* This file is part of Orfeo Toolbox
*
* https://www.orfeo-toolbox.org/
*
* 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
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* 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 "otbVectorImage.h"
#include "otbImageFileReader.h"
#include "otbImageFileWriter.h"
#include "otbPrintableImageFilter.h"
/* Example usage:
./ICAExample Input/wv2_cannes_8bands.tif \
Output/FastICAOutput.tif \
Output/InverseFastICAOutput.tif \
Output/FastICA-input-pretty.png \
Output/FastICA-output-pretty.png \
Output/FastICA-invoutput-pretty.png \
8 \
20 \
1.
*/
// This example illustrates the use of the
// \doxygen{otb}{FastICAImageFilter}.
// This filter computes a Fast Independent Components Analysis transform.
//
// Like Principal Components Analysis, Independent Component Analysis
// \cite{jutten1991blind} computes a set of
// orthogonal linear combinations, but the criterion of Fast ICA is
// different: instead of maximizing variance, it tries to maximize
// statistical independence between components.
//
// In the Fast ICA algorithm \cite{hyvarinen1999fast},
// statistical independence is measured by evaluating non-Gaussianity
// of the components, and the maximization is done in an iterative way.
// The first step required to use this filter is to include its header file.
#include "otbFastICAImageFilter.h"
int main(int itkNotUsed(argc), char* argv[])
{
using PixelType = double;
const unsigned int Dimension = 2;
const char* inputFileName = argv[1];
const char* outputFilename = argv[2];
const char* outputInverseFilename = argv[3];
const unsigned int numberOfPrincipalComponentsRequired(atoi(argv[7]));
const char* inpretty = argv[4];
const char* outpretty = argv[5];
const char* invoutpretty = argv[6];
unsigned int numIterations = atoi(argv[8]);
double mu = atof(argv[9]);
// We start by defining the types for the images, the reader, and
// the writer. We choose to work with a \doxygen{otb}{VectorImage},
// since we will produce a multi-channel image (the independent
// components) from a multi-channel input image.
using ImageType = otb::VectorImage<PixelType, Dimension>;
using ReaderType = otb::ImageFileReader<ImageType>;
using WriterType = otb::ImageFileWriter<ImageType>;
// We instantiate now the image reader and we set the image file name.
ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName(inputFileName);
// We define the type for the filter. It is templated over the input
// and the output image types and also the transformation direction. The
// internal structure of this filter is a filter-to-filter like structure.
// We can now the instantiate the filter.
using FastICAFilterType = otb::FastICAImageFilter<ImageType, ImageType, otb::Transform::FORWARD>;
FastICAFilterType::Pointer FastICAfilter = FastICAFilterType::New();
// We then set the number of independent
// components required as output. We can choose to get less ICs than
// the number of input bands.
FastICAfilter->SetNumberOfPrincipalComponentsRequired(numberOfPrincipalComponentsRequired);
// We set the number of iterations of the ICA algorithm.
FastICAfilter->SetNumberOfIterations(numIterations);
// We also set the $\mu$ parameter.
FastICAfilter->SetMu(mu);
// We now instantiate the writer and set the file name for the
// output image.
WriterType::Pointer writer = WriterType::New();
writer->SetFileName(outputFilename);
// We finally plug the pipeline and trigger the ICA computation with
// the method \code{Update()} of the writer.
FastICAfilter->SetInput(reader->GetOutput());
writer->SetInput(FastICAfilter->GetOutput());
writer->Update();
// \doxygen{otb}{FastICAImageFilter} allows also to compute inverse
// transformation from ICA coefficients. In reverse mode, the
// covariance matrix or the transformation matrix
// (which may not be square) has to be given.
using InvFastICAFilterType = otb::FastICAImageFilter<ImageType, ImageType, otb::Transform::INVERSE>;
InvFastICAFilterType::Pointer invFilter = InvFastICAFilterType::New();
invFilter->SetMeanValues(FastICAfilter->GetMeanValues());
invFilter->SetStdDevValues(FastICAfilter->GetStdDevValues());
invFilter->SetTransformationMatrix(FastICAfilter->GetTransformationMatrix());
invFilter->SetPCATransformationMatrix(FastICAfilter->GetPCATransformationMatrix());
invFilter->SetInput(FastICAfilter->GetOutput());
WriterType::Pointer invWriter = WriterType::New();
invWriter->SetFileName(outputInverseFilename);
invWriter->SetInput(invFilter->GetOutput());
invWriter->Update();
// Figure~\ref{fig:FastICA_FILTER} shows the result of applying forward
// and reverse FastICA transformation to a 8 bands Worldview2 image.
// \begin{figure}
// \center
// \includegraphics[width=0.32\textwidth]{FastICA-input-pretty.eps}
// \includegraphics[width=0.32\textwidth]{FastICA-output-pretty.eps}
// \includegraphics[width=0.32\textwidth]{FastICA-invoutput-pretty.eps}
// \itkcaption[PCA Filter (forward trasnformation)]{Result of applying the
// \doxygen{otb}{FastICAImageFilter} to an image. From left
// to right:
// original image, color composition with first three independent
// components and output of the
// inverse mode (the input RGB image).}
// \label{fig:FastICA_FILTER}
// \end{figure}
// This is for rendering in software guide
using PrintFilterType = otb::PrintableImageFilter<ImageType, ImageType>;
using VisuImageType = PrintFilterType::OutputImageType;
using VisuWriterType = otb::ImageFileWriter<VisuImageType>;
PrintFilterType::Pointer inputPrintFilter = PrintFilterType::New();
PrintFilterType::Pointer outputPrintFilter = PrintFilterType::New();
PrintFilterType::Pointer invertOutputPrintFilter = PrintFilterType::New();
VisuWriterType::Pointer inputVisuWriter = VisuWriterType::New();
VisuWriterType::Pointer outputVisuWriter = VisuWriterType::New();
VisuWriterType::Pointer invertOutputVisuWriter = VisuWriterType::New();
inputPrintFilter->SetInput(reader->GetOutput());
inputPrintFilter->SetChannel(5);
inputPrintFilter->SetChannel(3);
inputPrintFilter->SetChannel(2);
outputPrintFilter->SetInput(FastICAfilter->GetOutput());
outputPrintFilter->SetChannel(1);
outputPrintFilter->SetChannel(2);
outputPrintFilter->SetChannel(3);
invertOutputPrintFilter->SetInput(invFilter->GetOutput());
invertOutputPrintFilter->SetChannel(5);
invertOutputPrintFilter->SetChannel(3);
invertOutputPrintFilter->SetChannel(2);
inputVisuWriter->SetInput(inputPrintFilter->GetOutput());
outputVisuWriter->SetInput(outputPrintFilter->GetOutput());
invertOutputVisuWriter->SetInput(invertOutputPrintFilter->GetOutput());
inputVisuWriter->SetFileName(inpretty);
outputVisuWriter->SetFileName(outpretty);
invertOutputVisuWriter->SetFileName(invoutpretty);
inputVisuWriter->Update();
outputVisuWriter->Update();
invertOutputVisuWriter->Update();
return EXIT_SUCCESS;
}
|
