/usr/include/OTB-5.8/otbLocalHistogramImageFunction.txx is in libotb-dev 5.8.0+dfsg-3.
This file is owned by root:root, with mode 0o644.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 | /*=========================================================================
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.
=========================================================================*/
#ifndef otbLocalHistogramImageFunction_txx
#define otbLocalHistogramImageFunction_txx
#include "otbLocalHistogramImageFunction.h"
#include "itkConstNeighborhoodIterator.h"
#include "itkExtractImageFilter.h"
#include "otbMath.h"
namespace otb
{
/**
* Constructor
*/
template <class TInputImage, class TCoordRep>
LocalHistogramImageFunction<TInputImage, TCoordRep>
::LocalHistogramImageFunction() :
m_NeighborhoodRadius(1), m_NumberOfHistogramBins(128), m_HistogramMin(0), m_HistogramMax(1), m_GaussianSmoothing(true)
{
}
template <class TInputImage, class TCoordRep>
void
LocalHistogramImageFunction<TInputImage, TCoordRep>
::PrintSelf(std::ostream& os, itk::Indent indent) const
{
this->Superclass::PrintSelf(os, indent);
os << indent << " Neighborhood radius value : " << this->GetNeighborhoodRadius() << std::endl;
os << indent << " Number Of Histogram Bins : " << this->GetNumberOfHistogramBins() << std::endl;
os << indent << " Histogram Minimum : " << this->GetHistogramMin() << std::endl;
os << indent << " Histogram Maximum : " << this->GetHistogramMax() << std::endl;
}
template <class TInputImage, class TCoordRep>
typename LocalHistogramImageFunction<TInputImage, TCoordRep>::OutputType
LocalHistogramImageFunction<TInputImage, TCoordRep>
::EvaluateAtIndex(const IndexType& index) const
{
typename HistogramType::Pointer histogram = HistogramType::New();
typename HistogramType::SizeType size(this->GetInputImage()->GetNumberOfComponentsPerPixel());
size.Fill(this->GetNumberOfHistogramBins());
typename HistogramType::MeasurementVectorType lowerBound(this->GetInputImage()->GetNumberOfComponentsPerPixel());
typename HistogramType::MeasurementVectorType upperBound(this->GetInputImage()->GetNumberOfComponentsPerPixel());
lowerBound.Fill( static_cast<typename HistogramType::MeasurementType>(this->GetHistogramMin()) );
upperBound.Fill( static_cast<typename HistogramType::MeasurementType>(this->GetHistogramMax()) );
histogram->SetMeasurementVectorSize(this->GetInputImage()->GetNumberOfComponentsPerPixel());
histogram->Initialize(size, lowerBound, upperBound );
histogram->SetToZero();
// Check for input image
if( !this->GetInputImage() )
{
return histogram;
}
// Check for out of buffer
if ( !this->IsInsideBuffer( index ) )
{
return histogram;
}
// Create an N-d neighborhood kernel, using a zeroflux boundary condition
typename InputImageType::SizeType kernelSize;
kernelSize.Fill( m_NeighborhoodRadius );
itk::ConstNeighborhoodIterator<InputImageType>
it(kernelSize, this->GetInputImage(), this->GetInputImage()->GetBufferedRegion());
// Set the iterator at the desired location
it.SetLocation(index);
// Define a gaussian kernel around the center location
double squaredRadius = m_NeighborhoodRadius * m_NeighborhoodRadius;
double squaredSigma = 0.25 * squaredRadius;
// Offset to be used in the loops
typename InputImageType::OffsetType offset;
// Fill the histogram
for(int i = -(int)m_NeighborhoodRadius; i< (int)m_NeighborhoodRadius; ++i)
{
for(int j = -(int)m_NeighborhoodRadius; j< (int)m_NeighborhoodRadius; ++j)
{
// Check if the current pixel lies within a disc of radius m_NeighborhoodRadius
double currentSquaredRadius = i*i+j*j;
if(currentSquaredRadius < squaredRadius)
{
// If so, compute the gaussian weighting (this could be
// computed once for all for the sake of optimisation) if necessary
double gWeight = 1.;
if(m_GaussianSmoothing)
{
gWeight = (1/vcl_sqrt(otb::CONST_2PI*squaredSigma)) * vcl_exp(- currentSquaredRadius/(2*squaredSigma));
}
// Compute pixel location
offset[0]=i;
offset[1]=j;
// Get the current value
typename HistogramType::MeasurementVectorType sample(this->GetInputImage()->GetNumberOfComponentsPerPixel());
sample[0] = it.GetPixel(offset);
// Populate histogram
histogram->IncreaseFrequencyOfMeasurement(sample, gWeight);
}
}
}
return histogram;
}
} // namespace otb
#endif
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