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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.
*/
#ifndef otbVarianceImageFilter_hxx
#define otbVarianceImageFilter_hxx
#include "otbVarianceImageFilter.h"
#include "itkConstNeighborhoodIterator.h"
#include "itkNeighborhoodInnerProduct.h"
#include "itkImageRegionIterator.h"
#include "itkNeighborhoodAlgorithm.h"
#include "itkOffset.h"
#include "itkProgressReporter.h"
namespace otb
{
template <class TInputImage, class TOutputImage>
VarianceImageFilter<TInputImage, TOutputImage>::VarianceImageFilter()
{
m_Radius.Fill(1);
}
template <class TInputImage, class TOutputImage>
void VarianceImageFilter<TInputImage, TOutputImage>::GenerateInputRequestedRegion()
{
// call the superclass' implementation of this method
Superclass::GenerateInputRequestedRegion();
// get pointers to the input and output
typename Superclass::InputImagePointer inputPtr = const_cast<TInputImage*>(this->GetInput());
typename Superclass::OutputImagePointer outputPtr = this->GetOutput();
if (!inputPtr || !outputPtr)
{
return;
}
// get a copy of the input requested region (should equal the output
// requested region)
typename TInputImage::RegionType inputRequestedRegion;
inputRequestedRegion = inputPtr->GetRequestedRegion();
// pad the input requested region by the operator radius
inputRequestedRegion.PadByRadius(m_Radius);
// crop the input requested region at the input's largest possible region
if (inputRequestedRegion.Crop(inputPtr->GetLargestPossibleRegion()))
{
inputPtr->SetRequestedRegion(inputRequestedRegion);
return;
}
else
{
// Couldn't crop the region (requested region is outside the largest
// possible region). Throw an exception.
// store what we tried to request (prior to trying to crop)
inputPtr->SetRequestedRegion(inputRequestedRegion);
// build an exception
itk::InvalidRequestedRegionError e(__FILE__, __LINE__);
e.SetLocation(ITK_LOCATION);
e.SetDescription("Requested region is (at least partially) outside the largest possible region.");
e.SetDataObject(inputPtr);
throw e;
}
}
template <class TInputImage, class TOutputImage>
void VarianceImageFilter<TInputImage, TOutputImage>::ThreadedGenerateData(const OutputImageRegionType& outputRegionForThread, itk::ThreadIdType threadId)
{
unsigned int i;
itk::ZeroFluxNeumannBoundaryCondition<InputImageType> nbc;
itk::ConstNeighborhoodIterator<InputImageType> bit;
itk::ImageRegionIterator<OutputImageType> it;
// Allocate output
typename OutputImageType::Pointer output = this->GetOutput();
typename InputImageType::ConstPointer input = this->GetInput();
// Find the data-set boundary "faces"
typename itk::NeighborhoodAlgorithm::ImageBoundaryFacesCalculator<InputImageType>::FaceListType faceList;
itk::NeighborhoodAlgorithm::ImageBoundaryFacesCalculator<InputImageType> bC;
faceList = bC(input, outputRegionForThread, m_Radius);
typename itk::NeighborhoodAlgorithm::ImageBoundaryFacesCalculator<InputImageType>::FaceListType::iterator fit;
// support progress methods/callbacks
itk::ProgressReporter progress(this, threadId, outputRegionForThread.GetNumberOfPixels());
InputRealType sum;
InputRealType sumOfSquares;
// Process each of the boundary faces. These are N-d regions which border
// the edge of the buffer.
for (fit = faceList.begin(); fit != faceList.end(); ++fit)
{
bit = itk::ConstNeighborhoodIterator<InputImageType>(m_Radius, input, *fit);
unsigned int neighborhoodSize = bit.Size();
it = itk::ImageRegionIterator<OutputImageType>(output, *fit);
bit.OverrideBoundaryCondition(&nbc);
bit.GoToBegin();
while (!bit.IsAtEnd())
{
sum = itk::NumericTraits<InputRealType>::Zero;
sumOfSquares = itk::NumericTraits<InputRealType>::Zero;
for (i = 0; i < neighborhoodSize; ++i)
{
const InputRealType value = static_cast<InputRealType>(bit.GetPixel(i));
sum += value;
sumOfSquares += value * value;
}
// get the mean value
const double num = static_cast<double>(neighborhoodSize);
it.Set(static_cast<OutputPixelType>(sumOfSquares - (sum * sum / num)) / (num - 1.0));
++bit;
++it;
progress.CompletedPixel();
}
}
}
/**
* Standard "PrintSelf" method
*/
template <class TInputImage, class TOutput>
void VarianceImageFilter<TInputImage, TOutput>::PrintSelf(std::ostream& os, itk::Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "Radius: " << m_Radius << std::endl;
}
} // end namespace otb
#endif
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