MultivariateAlterationDetector.cxx

Example usage:

./MultivariateAlterationDetector Input/Spot5-Gloucester-before.tif \
                                 Input/Spot5-Gloucester-after.tif \
                                 Output/MADOutput.tif \
                                 Output/mad-input1.png \
                                 Output/mad-input2.png \
                                 Output/mad-output.png

Example source code (MultivariateAlterationDetector.cxx):

#include "otbVectorImage.h"
#include "otbImageFileReader.h"
#include "otbImageFileWriter.h"
#include "otbPrintableImageFilter.h"





// This example illustrates the class
// \doxygen{otb}{MultivariateAlterationChangeDetectorImageFilter},
// which implements the Multivariate Alteration Change Detector
// algorithm \cite{nielsen2007regularized}. This algorihtm allows
// performing change detection from a pair multi-band images, including
// images with different number of bands or modalities. Its output is
// a a multi-band image of change maps, each one being unccorrelated
// with the remaining. The number of bands of the output image is the
// minimum number of bands between the two input images.
//
// The algorithm works as follows. It tries to find two linear
// combinations of bands (one for each input images) which maximize
// correlation, and subtract these two linear combinitation, leading
// to the first change map. Then, it looks for a second set of linear
// combinations which are orthogonal to the first ones, a which
// maximize correlation, and use it as the second change map. This
// process is iterated until no more orthogonal linear combinations
// can be found.
//
// This algorithms has numerous advantages, such as radiometry scaling
// and shifting invariance and absence of parameters, but it can not
// be used on a pair of single band images (in this case the output is
// simply the difference between the two images).
//
// We start by including the corresponding header file.

#include "otbMultivariateAlterationDetectorImageFilter.h"

int main(int argc, char* argv[])
{

  if (argc < 6)
  {
    std::cerr << "Usage: " << std::endl;
    std::cerr << argv[0] << " inputImageFile1 inputImageFile2 outIn1Pretty outIn2Pretty outPretty"
              << "outputImageFile" << std::endl;
    return -1;
  }

  // Define the dimension of the images
  const unsigned int Dimension = 2;

  // We then define the types for the input images and for the
  // change image.

  typedef unsigned short                               InputPixelType;
  typedef float                                        OutputPixelType;
  typedef otb::VectorImage<InputPixelType, Dimension>  InputImageType;
  typedef otb::VectorImage<OutputPixelType, Dimension> OutputImageType;

  //  We can now declare the types for the reader. Since the images
  //  can be vey large, we will force the pipeline to use
  //  streaming. For this purpose, the file writer will be
  //  streamed. This is achieved by using the
  //  \doxygen{otb}{ImageFileWriter} class.

  typedef otb::ImageFileReader<InputImageType>  ReaderType;
  typedef otb::ImageFileWriter<OutputImageType> WriterType;


  // This is for rendering in software guide
  typedef otb::PrintableImageFilter<InputImageType, InputImageType>   InputPrintFilterType;
  typedef otb::PrintableImageFilter<OutputImageType, OutputImageType> OutputPrintFilterType;
  typedef InputPrintFilterType::OutputImageType                       VisuImageType;
  typedef otb::ImageFileWriter<VisuImageType>                         VisuWriterType;

  //  The \doxygen{otb}{MultivariateAlterationDetectorImageFilter} is templated over
  //  the type of the input images and the type of the generated change
  //  image.

  typedef otb::MultivariateAlterationDetectorImageFilter<InputImageType, OutputImageType> MADFilterType;

  //  The different elements of the pipeline can now be instantiated.

  ReaderType::Pointer    reader1   = ReaderType::New();
  ReaderType::Pointer    reader2   = ReaderType::New();
  WriterType::Pointer    writer    = WriterType::New();
  MADFilterType::Pointer madFilter = MADFilterType::New();

  const char* inputFilename1 = argv[1];
  const char* inputFilename2 = argv[2];
  const char* outputFilename = argv[3];
  const char* in1pretty      = argv[4];
  const char* in2pretty      = argv[5];
  const char* outpretty      = argv[6];
  //  We set the parameters of the different elements of the pipeline.

  reader1->SetFileName(inputFilename1);
  reader2->SetFileName(inputFilename2);
  writer->SetFileName(outputFilename);

  //  We build the pipeline by plugging all the elements together.

  madFilter->SetInput1(reader1->GetOutput());
  madFilter->SetInput2(reader2->GetOutput());
  writer->SetInput(madFilter->GetOutput());

  try
  {
    //  And then we can trigger the pipeline update, as usual.

    writer->Update();
  }
  catch (itk::ExceptionObject& err)
  {
    std::cout << "ExceptionObject caught !" << std::endl;
    std::cout << err << std::endl;
    return -1;
  }

  // Here we generate the figures
  InputPrintFilterType::Pointer  input1PrintFilter = InputPrintFilterType::New();
  InputPrintFilterType::Pointer  input2PrintFilter = InputPrintFilterType::New();
  OutputPrintFilterType::Pointer outputPrintFilter = OutputPrintFilterType::New();
  VisuWriterType::Pointer        input1VisuWriter  = VisuWriterType::New();
  VisuWriterType::Pointer        input2VisuWriter  = VisuWriterType::New();
  VisuWriterType::Pointer        outputVisuWriter  = VisuWriterType::New();

  input1PrintFilter->SetInput(reader1->GetOutput());
  input1PrintFilter->SetChannel(3);
  input1PrintFilter->SetChannel(2);
  input1PrintFilter->SetChannel(1);
  input2PrintFilter->SetInput(reader2->GetOutput());
  input2PrintFilter->SetChannel(3);
  input2PrintFilter->SetChannel(2);
  input2PrintFilter->SetChannel(1);
  outputPrintFilter->SetInput(madFilter->GetOutput());
  outputPrintFilter->SetChannel(3);
  outputPrintFilter->SetChannel(2);
  outputPrintFilter->SetChannel(1);

  input1VisuWriter->SetInput(input1PrintFilter->GetOutput());
  input2VisuWriter->SetInput(input2PrintFilter->GetOutput());
  outputVisuWriter->SetInput(outputPrintFilter->GetOutput());

  input1VisuWriter->SetFileName(in1pretty);
  input2VisuWriter->SetFileName(in2pretty);
  outputVisuWriter->SetFileName(outpretty);

  input1VisuWriter->Update();
  input2VisuWriter->Update();
  outputVisuWriter->Update();

  // Figure \ref{fig:MADCHDET} shows the
  // results of Multivariate Alteration Detector applied to a pair of
  // SPOT5 images before and after a flooding event.
  // \begin{figure}
  // \center \includegraphics[width=0.32\textwidth]{mad-input1.eps}
  // \includegraphics[width=0.32\textwidth]{mad-input2.eps}
  // \includegraphics[width=0.32\textwidth]{mad-output.eps}
  // \itkcaption[Multivariate Alteration Detection
  // Results]{Result of the Multivariate Alteration Detector results on
  // SPOT5 data before and after flooding.}  \label{fig:MADCHDET}
  // \end{figure}

  return EXIT_SUCCESS;
}