CorrelChDet.cxx 4.41 KB
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/*
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 * Copyright (C) 2005-2019 Centre National d'Etudes Spatiales (CNES)
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 *
 * 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.
 */
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#include "otbImageFileReader.h"
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#include "otbImageFileWriter.h"
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#include "otbImage.h"
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#include "itkShiftScaleImageFilter.h"
#include "otbCommandProgressUpdate.h"
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#include "otbCorrelationChangeDetector.h"
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/* Example usage:
./CorrelChDet Input/ERSBefore.png Input/ERSAfter.png Output/CorrChDet.tif 15
*/

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

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  if (argc < 5)
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  {
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    std::cerr << "Usage: " << std::endl;
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    std::cerr << argv[0] << " inputImageFile1 inputImageFile2 "
              << "outputImageFile radius" << std::endl;
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    return -1;
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  }
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  // Define the dimension of the images
  const unsigned int Dimension = 2;

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  // We start by declaring the types for the two input images, the
  // change image and the image to be stored in a file for visualization.
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  using InternalPixelType = float;
  using OutputPixelType   = unsigned char;
  using InputImageType1   = otb::Image<InternalPixelType, Dimension>;
  using InputImageType2   = otb::Image<InternalPixelType, Dimension>;
  using ChangeImageType   = otb::Image<InternalPixelType, Dimension>;
  using OutputImageType   = otb::Image<OutputPixelType, Dimension>;
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  // We can now declare the types for the readers. Since the images
  // can be very large, we will force the pipeline to use
  // streaming. For this purpose, the file writer will be
  // streamed.
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  using ReaderType1 = otb::ImageFileReader<InputImageType1>;
  using ReaderType2 = otb::ImageFileReader<InputImageType2>;
  using WriterType  = otb::ImageFileWriter<OutputImageType>;
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  // The change detector will give a response which is normalized
  // between 0 and 1.
  // Before saving the image to a file in, for instance, PNG format, we will
  // rescale the results of the change detection in order to use all
  // the output pixel type range of values.
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  using RescalerType = itk::ShiftScaleImageFilter<ChangeImageType, OutputImageType>;
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  // The CorrelationChangeDetector is templated over
  // the types of the two input images and the type of the generated change
  // image.
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  using FilterType = otb::CorrelationChangeDetector<InputImageType1, InputImageType2, ChangeImageType>;
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  // The different elements of the pipeline can now be instantiated.
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  ReaderType1::Pointer  reader1        = ReaderType1::New();
  ReaderType2::Pointer  reader2        = ReaderType2::New();
  WriterType::Pointer   writer         = WriterType::New();
  FilterType::Pointer   filter         = FilterType::New();
  RescalerType::Pointer rescaler       = RescalerType::New();
  const char*           inputFilename1 = argv[1];
  const char*           inputFilename2 = argv[2];
  const char*           outputFilename = argv[3];
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  // We set the parameters of the different elements of the pipeline.
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  reader1->SetFileName(inputFilename1);
  reader2->SetFileName(inputFilename2);
  writer->SetFileName(outputFilename);
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  float scale = itk::NumericTraits<OutputPixelType>::max();
  rescaler->SetScale(scale);
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  // The only parameter for this change detector is the radius of
  // the window used for computing the correlation coefficient.
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  filter->SetRadius(atoi(argv[4]));
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  // We build the pipeline by plugging all the elements together.
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  filter->SetInput1(reader1->GetOutput());
  filter->SetInput2(reader2->GetOutput());
  rescaler->SetInput(filter->GetOutput());
  writer->SetInput(rescaler->GetOutput());
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  // Since the processing time of large images can be long, it is
  // interesting to monitor the evolution of the computation. In
  // order to do so, the change detectors can use the
  // command/observer design pattern. This is easily done by
  // attaching an observer to the filter.
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  using CommandType = otb::CommandProgressUpdate<FilterType>;
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  CommandType::Pointer observer = CommandType::New();
  filter->AddObserver(itk::ProgressEvent(), observer);

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  writer->Update();
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}