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/*=========================================================================
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.
=========================================================================*/
// Software Guide : BeginCommandLineArgs
// INPUTS: {StereoFixed.png}, {StereoMoving.png}
// OUTPUTS: {deformationFieldOutput-horizontal.png}, {deformationFieldOutput-vertical.png}, {resampledOutput2.png}
// 5 1.0 2
// Software Guide : EndCommandLineArgs
// Software Guide : BeginLatex
//
// This example demonstrates the use of the \doxygen{otb}{NCCRegistrationFilter}. This filter performs deformation estimation
// by optimising a PDE based on the normalized correlation coefficient. It uses the finite difference solver hierarchy.
//
// The first step toward the use of these filters is to include the proper header files.
//
// Software Guide : EndLatex
#include "otbImageFileWriter.h"
#include "otbImageFileReader.h"
#include "otbCommandLineArgumentParser.h"
// Software Guide : BeginCodeSnippet
#include "otbNCCRegistrationFilter.h"
#include "itkRecursiveGaussianImageFilter.h"
#include "otbWarpImageFilter.h"
// Software Guide : EndCodeSnippet
#include "otbImageOfVectorsToMonoChannelExtractROI.h"
#include "itkUnaryFunctorImageFilter.h"
#include "itkRescaleIntensityImageFilter.h"
#include "itkCastImageFilter.h"
#include <iostream>
int main(int argc, char** argv)
{
if (argc != 9)
{
std::cerr << "Usage: " << argv[0];
std::cerr <<
" fixedFileName movingFileName fieldOutNameHorizontal fieldOutNameVertical imageOutName ";
std::cerr << "explorationSize bluringSigma nbIterations ";
return EXIT_FAILURE;
}
const unsigned int ImageDimension = 2;
typedef double PixelType;
typedef itk::Vector<double, ImageDimension> DisplacementPixelType;
typedef unsigned char OutputPixelType;
typedef otb::Image<OutputPixelType, ImageDimension> OutputImageType;
// Software Guide : BeginLatex
//
// Several type of \doxygen{otb}{Image} are required to represent the reference image (fixed)
// the image we want to register (moving) and the deformation field.
//
// Software Guide : EndLatex
//Allocate Images
// Software Guide : BeginCodeSnippet
typedef otb::Image<PixelType, ImageDimension> MovingImageType;
typedef otb::Image<PixelType, ImageDimension> FixedImageType;
typedef otb::Image<DisplacementPixelType,
ImageDimension> DisplacementFieldType;
// Software Guide : EndCodeSnippet
typedef otb::ImageFileReader<FixedImageType> FixedReaderType;
FixedReaderType::Pointer fReader = FixedReaderType::New();
fReader->SetFileName(argv[1]);
typedef otb::ImageFileReader<MovingImageType> MovingReaderType;
MovingReaderType::Pointer mReader = MovingReaderType::New();
mReader->SetFileName(argv[2]);
// Software Guide : BeginLatex
//
// To make the correlation estimation more robust, the first
// required step is to blur the input images. This is done using the
// \doxygen{itk}{RecursiveGaussianImageFilter}:
//
// Software Guide : EndLatex
//Blur input images
// Software Guide : BeginCodeSnippet
typedef itk::RecursiveGaussianImageFilter<FixedImageType,
FixedImageType> FixedBlurType;
FixedBlurType::Pointer fBlur = FixedBlurType::New();
fBlur->SetInput(fReader->GetOutput());
fBlur->SetSigma(atof(argv[7]));
typedef itk::RecursiveGaussianImageFilter<MovingImageType,
MovingImageType> MovingBlurType;
MovingBlurType::Pointer mBlur = MovingBlurType::New();
mBlur->SetInput(mReader->GetOutput());
mBlur->SetSigma(atof(argv[7]));
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Now, we need to instantiate the NCCRegistrationFilter which is going to perform the registration:
//
// Software Guide : EndLatex
//Create the filter
// Software Guide : BeginCodeSnippet
typedef otb::NCCRegistrationFilter<FixedImageType,
MovingImageType,
DisplacementFieldType>
RegistrationFilterType;
RegistrationFilterType::Pointer registrator = RegistrationFilterType::New();
registrator->SetMovingImage(mBlur->GetOutput());
registrator->SetFixedImage(fBlur->GetOutput());
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Some parameters need to be specified to the NCCRegistrationFilter:
// \begin{itemize}
// \item The area where the search is performed. This area is defined by its radius:
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef RegistrationFilterType::RadiusType RadiusType;
RadiusType radius;
radius[0] = atoi(argv[6]);
radius[1] = atoi(argv[6]);
registrator->SetNCCRadius(radius);
// Software Guide : EndCodeSnippet
std::cout << "NCC radius " << registrator->GetNCCRadius() << std::endl;
// Software Guide : BeginLatex
//
// \item The number of iterations for the PDE resolution:
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
registrator->SetNumberOfIterations(atoi(argv[8]));
// Software Guide : EndCodeSnippet
// registrator->GetDisplacementField();
// Software Guide : BeginLatex
//
// \end{itemize}
// The execution of the NCCRegistrationFilter will be triggered by
// the \code{Update()} call on the writer at the end of the
// pipeline. Make sure to use a
// \doxygen{otb}{ImageFileWriter} if you want to benefit
// from the streaming features.
//
// Software Guide : EndLatex
typedef otb::ImageOfVectorsToMonoChannelExtractROI<DisplacementFieldType,
MovingImageType>
ChannelExtractionFilterType;
ChannelExtractionFilterType::Pointer channelExtractor =
ChannelExtractionFilterType::New();
channelExtractor->SetInput(registrator->GetOutput());
channelExtractor->SetChannel(1);
typedef itk::RescaleIntensityImageFilter<MovingImageType,
OutputImageType> RescalerType;
RescalerType::Pointer fieldRescaler = RescalerType::New();
fieldRescaler->SetInput(channelExtractor->GetOutput());
fieldRescaler->SetOutputMaximum(255);
fieldRescaler->SetOutputMinimum(0);
typedef otb::ImageFileWriter<OutputImageType> DFWriterType;
DFWriterType::Pointer dfWriter = DFWriterType::New();
dfWriter->SetFileName(argv[3]);
dfWriter->SetInput(fieldRescaler->GetOutput());
dfWriter->Update();
channelExtractor->SetChannel(2);
dfWriter->SetFileName(argv[4]);
dfWriter->Update();
typedef otb::WarpImageFilter<MovingImageType, MovingImageType,
DisplacementFieldType> WarperType;
WarperType::Pointer warper = WarperType::New();
MovingImageType::PixelType padValue = 4.0;
warper->SetInput(mReader->GetOutput());
warper->SetDisplacementField(registrator->GetOutput());
warper->SetEdgePaddingValue(padValue);
typedef itk::CastImageFilter<MovingImageType, OutputImageType> CastFilterType;
CastFilterType::Pointer caster = CastFilterType::New();
caster->SetInput(warper->GetOutput());
typedef otb::ImageFileWriter<OutputImageType> WriterType;
WriterType::Pointer writer = WriterType::New();
writer->SetFileName(argv[5]);
writer->SetInput(caster->GetOutput());
writer->Update();
// Software Guide : BeginLatex
//
// Figure~\ref{fig:NCCRegistrationFilterOUTPUT} shows the result of
// applying the disparity map estimation.
//
// \begin{figure}
// \center
// \includegraphics[width=0.40\textwidth]{StereoFixed.eps}
// \includegraphics[width=0.40\textwidth]{StereoMoving.eps}
// \includegraphics[width=0.40\textwidth]{deformationFieldOutput-horizontal.eps}
// \includegraphics[width=0.40\textwidth]{deformationFieldOutput-vertical.eps}
// \itkcaption[Displacement field and resampling from NCC registration]{From left
// to right and top to bottom: fixed input image, moving image with a low stereo angle,
// estimated deformation field in the horizontal direction, estimated deformation field in the vertical direction.}
// \label{fig:NCCRegistrationFilterOUTPUT}
// \end{figure}
//
// Software Guide : EndLatex
return EXIT_SUCCESS;
}
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