This file is indexed.

/usr/include/ITK-4.5/itkVectorAnisotropicDiffusionFunction.hxx is in libinsighttoolkit4-dev 4.5.0-3.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  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
/*=========================================================================
 *
 *  Copyright Insight Software Consortium
 *
 *  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.txt
 *
 *  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 __itkVectorAnisotropicDiffusionFunction_hxx
#define __itkVectorAnisotropicDiffusionFunction_hxx
#include "itkVectorAnisotropicDiffusionFunction.h"

#include "itkConstNeighborhoodIterator.h"
#include "itkVectorNeighborhoodInnerProduct.h"
#include "itkNeighborhoodAlgorithm.h"
#include "itkDerivativeOperator.h"

namespace itk
{
template< typename TImage >
void
VectorAnisotropicDiffusionFunction< TImage >
::CalculateAverageGradientMagnitudeSquared(TImage *ip)
{
  typedef ConstNeighborhoodIterator< TImage >                           RNI_type;
  typedef ConstNeighborhoodIterator< TImage >                           SNI_type;
  typedef NeighborhoodAlgorithm::ImageBoundaryFacesCalculator< TImage > BFC_type;

  unsigned int i, j;
  //  ZeroFluxNeumannBoundaryCondition<TImage>  bc;
  double        accumulator;
  PixelType     val;
  SizeValueType counter;
  BFC_type      bfc;
  typename BFC_type::FaceListType faceList;
  typename RNI_type::RadiusType radius;
  typename BFC_type::FaceListType::iterator fit;

  VectorNeighborhoodInnerProduct< TImage > SIP;
  VectorNeighborhoodInnerProduct< TImage > IP;
  RNI_type                                 iterator_list[ImageDimension];
  SNI_type                                 face_iterator_list[ImageDimension];
  typedef typename PixelType::ValueType PixelValueType;
  DerivativeOperator< PixelValueType, ImageDimension > operator_list[ImageDimension];

  // Set up the derivative operators, one for each dimension
  for ( i = 0; i < ImageDimension; ++i )
    {
    operator_list[i].SetOrder(1);
    operator_list[i].SetDirection(i);
    operator_list[i].CreateDirectional();
    radius[i] = operator_list[i].GetRadius()[i];
    }

  // Get the various region "faces" that are on the data set boundary.
  faceList = bfc(ip, ip->GetRequestedRegion(), radius);
  fit      = faceList.begin();

  // Now do the actual processing
  accumulator = 0.0;
  counter     = NumericTraits<SizeValueType>::Zero;

  // First process the non-boundary region

  // Instead of maintaining a single N-d neighborhood of pointers,
  // we maintain a list of 1-d neighborhoods along each axial direction.
  // This is more efficient for higher dimensions.
  for ( i = 0; i < ImageDimension; ++i )
    {
    iterator_list[i] = RNI_type(operator_list[i].GetRadius(), ip, *fit);
    iterator_list[i].GoToBegin();
    }
  while ( !iterator_list[0].IsAtEnd() )
    {
    counter++;
    for ( i = 0; i < ImageDimension; ++i )
      {
      val = IP(iterator_list[i], operator_list[i]);
      for ( j = 0; j < VectorDimension; ++j )
        {
        accumulator += val[j] * val[j];
        }
      ++iterator_list[i];
      }
    }

  // Go on to the next region(s).  These are on the boundary faces.
  ++fit;
  while ( fit != faceList.end() )
    {
    for ( i = 0; i < ImageDimension; ++i )
      {
      face_iterator_list[i] = SNI_type(operator_list[i].GetRadius(), ip, *fit);
      face_iterator_list[i].GoToBegin();
      }

    while ( !face_iterator_list[0].IsAtEnd() )
      {
      counter++;
      for ( i = 0; i < ImageDimension; ++i )
        {
        val = SIP(face_iterator_list[i], operator_list[i]);
        for ( j = 0; j < VectorDimension; ++j )
          {
          accumulator += val[j] * val[j];
          }
        ++face_iterator_list[i];
        }
      }
    ++fit;
    }

  this->SetAverageGradientMagnitudeSquared( (double)accumulator / counter );
}
} // end namespace itk

#endif