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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223
|
/*=========================================================================
Program: ORFEO Toolbox
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt 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.
=========================================================================*/
#include "otbImage.h"
#include "otbImageFileReader.h"
#include "otbImageFileWriter.h"
#include "itkUnaryFunctorImageFilter.h"
#include "itkRescaleIntensityImageFilter.h"
// Software Guide : BeginCommandLineArgs
// INPUTS: {suburb2.jpeg}
// OUTPUTS: {EdgeDensityOutput.tif}, {PrettyEdgeDensityOutput.png}
// 7 50 10 1.0 0.01
// Software Guide : EndCommandLineArgs
// Software Guide : BeginLatex
//
// This example illustrates the use of the
// \doxygen{otb}{EdgeDensityImageFilter}.
// This filter computes a local density of edges on an image and can
// be useful to detect man made objects or urban areas, for
// instance. The filter has been implemented in a generic way, so that
// the way the edges are detected and the way their density is
// computed can be chosen by the user.
//
// The first step required to use this filter is to include its header file.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "otbEdgeDensityImageFilter.h"
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We will also include the header files for the edge detector (a
// Canny filter) and the density estimation (a simple count on a
// binary image).
//
// The first step required to use this filter is to include its header file.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkCannyEdgeDetectionImageFilter.h"
#include "otbBinaryImageDensityFunction.h"
// Software Guide : EndCodeSnippet
int main(int itkNotUsed(argc), char* argv[])
{
const char * infname = argv[1];
const char * outfname = argv[2];
const char * prettyfilename = argv[3];
const unsigned int radius = atoi(argv[4]);
/*--*/
const unsigned int Dimension = 2;
typedef float PixelType;
/** Variables for the canny detector*/
const PixelType upperThreshold = static_cast<PixelType>(atof(argv[5]));
const PixelType lowerThreshold = static_cast<PixelType>(atof(argv[6]));
const double variance = atof(argv[7]);
const double maximumError = atof(argv[8]);
// Software Guide : BeginLatex
//
// As usual, we start by defining the types for the images, the reader
// and the writer.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef otb::Image<PixelType, Dimension> ImageType;
typedef otb::ImageFileReader<ImageType> ReaderType;
typedef otb::ImageFileWriter<ImageType> WriterType;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We define now the type for the function which will be used by the
// edge density filter to estimate this density. Here we choose a
// function which counts the number of non null pixels per area. The
// function takes as template the type of the image to be processed.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef otb::BinaryImageDensityFunction<ImageType> CountFunctionType;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// These {\em non null pixels} will be the result of an edge
// detector. We use here the classical Canny edge detector, which is
// templated over the input and output image types.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::CannyEdgeDetectionImageFilter<ImageType, ImageType>
CannyDetectorType;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Finally, we can define the type for the edge density filter which
// takes as template the input and output image types, the edge
// detector type, and the count function type..
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef otb::EdgeDensityImageFilter<ImageType, ImageType, CannyDetectorType,
CountFunctionType> EdgeDensityFilterType;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We can now instantiate the different processing objects of the
// pipeline using the \code{New()} method.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
ReaderType::Pointer reader = ReaderType::New();
EdgeDensityFilterType::Pointer filter = EdgeDensityFilterType::New();
CannyDetectorType::Pointer cannyFilter = CannyDetectorType::New();
WriterType::Pointer writer = WriterType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The edge detection filter needs to be instantiated because we
// need to set its parameters. This is what we do here for the Canny
// filter.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
cannyFilter->SetUpperThreshold(upperThreshold);
cannyFilter->SetLowerThreshold(lowerThreshold);
cannyFilter->SetVariance(variance);
cannyFilter->SetMaximumError(maximumError);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// After that, we can pass the edge detector to the filter which
// will be used it internally.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
filter->SetDetector(cannyFilter);
filter->SetNeighborhoodRadius(radius);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Finally, we set the file names for the input and the output
// images and we plug the pipeline. The \code{Update()} method of
// the writer will trigger the processing.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
reader->SetFileName(infname);
writer->SetFileName(outfname);
filter->SetInput(reader->GetOutput());
writer->SetInput(filter->GetOutput());
writer->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
// Figure~\ref{fig:EDGEDENSITY_FILTER} shows the result of applying
// the edge density filter to an image.
// \begin{figure}
// \center
// \includegraphics[width=0.25\textwidth]{suburb2.eps}
// \includegraphics[width=0.25\textwidth]{PrettyEdgeDensityOutput.eps}
// \itkcaption[Edge Density Filter]{Result of applying the
// \doxygen{otb}{EdgeDensityImageFilter} to an image. From left to right :
// original image, edge density.}
// \label{fig:EDGEDENSITY_FILTER}
// \end{figure}
//
// Software Guide : EndLatex
/************* Image for printing **************/
typedef otb::Image<unsigned char, 2> OutputImageType;
typedef itk::RescaleIntensityImageFilter<ImageType, OutputImageType>
RescalerType;
RescalerType::Pointer rescaler = RescalerType::New();
rescaler->SetOutputMinimum(0);
rescaler->SetOutputMaximum(255);
rescaler->SetInput(filter->GetOutput());
typedef otb::ImageFileWriter<OutputImageType> OutputWriterType;
OutputWriterType::Pointer outwriter = OutputWriterType::New();
outwriter->SetFileName(prettyfilename);
outwriter->SetInput(rescaler->GetOutput());
outwriter->Update();
return EXIT_SUCCESS;
}
|