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/*
* 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.
*/
/* Example usage:
./ScalingPipeline Input/QB_Suburb.png Output/TutorialsScalingPipelineOutput.png
*/
// This example illustrates the use of the
// \doxygen{itk}{RescaleIntensityImageFilter} to convert
// the result for proper display.
//
// We include the required header including the header
// for the \doxygen{itk}{CannyEdgeDetectionImageFilter} and the
// \doxygen{itk}{RescaleIntensityImageFilter}.
#include "otbImage.h"
#include "otbImageFileReader.h"
#include "otbImageFileWriter.h"
#include "itkUnaryFunctorImageFilter.h"
#include "itkCannyEdgeDetectionImageFilter.h"
#include "itkRescaleIntensityImageFilter.h"
int main(int argc, char* argv[])
{
if (argc != 3)
{
std::cerr << "Usage: " << argv[0] << " <input_filename> <output_filename>" << std::endl;
}
// We need to declare two different image types, one for the internal
// processing and one to output the results:
using PixelType = double;
using ImageType = otb::Image<PixelType, 2>;
using OutputPixelType = unsigned char;
using OutputImageType = otb::Image<OutputPixelType, 2>;
// We declare the reader with the image template using the pixel type
// double. It is worth noticing that this instantiation does not imply
// anything about the type of the input image. The original image can be
// anything, the reader will just convert the result to double.
//
// The writer is templated with the unsigned char image to be able to save
// the result on one byte images (like png for example).
using ReaderType = otb::ImageFileReader<ImageType>;
ReaderType::Pointer reader = ReaderType::New();
using WriterType = otb::ImageFileWriter<OutputImageType>;
WriterType::Pointer writer = WriterType::New();
reader->SetFileName(argv[1]);
writer->SetFileName(argv[2]);
// Now we are declaring the edge detection filter which is going to work with
// double input and output.
using FilterType = itk::CannyEdgeDetectionImageFilter<ImageType, ImageType>;
FilterType::Pointer filter = FilterType::New();
// Here comes the interesting part: we declare the
// \doxygen{itk}{RescaleIntensityImageFilter}. The input
// image type is the output type of the edge detection
// filter. The output type is the same as the input type
// of the writer.
//
// Desired minimum and maximum values for the output are
// specified by the methods \code{SetOutputMinimum()} and
// \code{SetOutputMaximum()}.
//
// This filter will actually rescale all the pixels of
// the image but also cast the type of these pixels.
using RescalerType = itk::RescaleIntensityImageFilter<ImageType, OutputImageType>;
RescalerType::Pointer rescaler = RescalerType::New();
rescaler->SetOutputMinimum(0);
rescaler->SetOutputMaximum(255);
// Let's plug the pipeline:
filter->SetInput(reader->GetOutput());
rescaler->SetInput(filter->GetOutput());
writer->SetInput(rescaler->GetOutput());
// And finally, we trigger the pipeline execution calling the Update()
// method on the writer
writer->Update();
return EXIT_SUCCESS;
}
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