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
|
/*
* Copyright (C) 2005-2022 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:
./PCAExample Input/wv2_cannes_8bands.tif \
Output/PCAOutput.tif \
Output/InversePCAOutput.tif \
Output/input-pretty.png \
Output/output-pretty.png \
Output/invoutput-pretty.png \
8
*/
// This example illustrates the use of the
// \doxygen{otb}{PCAImageFilter}.
// This filter computes a Principal Component Analysis using an
// efficient method based on the inner product in order to compute the
// covariance matrix.
//
// The first step required to use this filter is to include its header file.
#include "otbPCAImageFilter.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];
// We start by defining the types for the images and the reader and
// the writer. We choose to work with a \doxygen{otb}{VectorImage},
// since we will produce a multi-channel image (the principal
// 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 PCAFilterType = otb::PCAImageFilter<ImageType, ImageType, otb::Transform::FORWARD>;
PCAFilterType::Pointer pcafilter = PCAFilterType::New();
// The only parameter needed for the PCA is the number of principal
// components required as output. Principal components are linear combination of input components
// (here the input image bands),
// which are selected using Singular Value Decomposition eigen vectors sorted by eigen value.
// We can choose to get less Principal Components than
// the number of input bands.
pcafilter->SetNumberOfPrincipalComponentsRequired(numberOfPrincipalComponentsRequired);
// 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 PCA computation with
// the method \code{Update()} of the writer.
pcafilter->SetInput(reader->GetOutput());
writer->SetInput(pcafilter->GetOutput());
writer->Update();
// \doxygen{otb}{PCAImageFilter} allows also to compute inverse
// transformation from PCA coefficients. In reverse mode, the
// covariance matrix or the transformation matrix
// (which may not be square) has to be given.
using InvPCAFilterType = otb::PCAImageFilter<ImageType, ImageType, otb::Transform::INVERSE>;
InvPCAFilterType::Pointer invFilter = InvPCAFilterType::New();
invFilter->SetInput(pcafilter->GetOutput());
invFilter->SetTransformationMatrix(pcafilter->GetTransformationMatrix());
WriterType::Pointer invWriter = WriterType::New();
invWriter->SetFileName(outputInverseFilename);
invWriter->SetInput(invFilter->GetOutput());
invWriter->Update();
// Figure~\ref{fig:PCA_FILTER} shows the result of applying forward
// and reverse PCA transformation to a 8 bands Worldview2 image.
// \begin{figure}
// \center
// \includegraphics[width=0.32\textwidth]{input-pretty.eps}
// \includegraphics[width=0.32\textwidth]{output-pretty.eps}
// \includegraphics[width=0.32\textwidth]{invoutput-pretty.eps}
// \itkcaption[PCA Filter (forward trasnformation)]{Result of applying the
// \doxygen{otb}{PCAImageFilter} to an image. From left
// to right:
// original image, color composition with first three principal
// components and output of the
// inverse mode (the input RGB image).}
// \label{fig:PCA_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(pcafilter->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;
}
|
