/usr/include/ITK-4.5/itkYenThresholdCalculator.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.
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*
* 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 __itkYenThresholdCalculator_hxx
#define __itkYenThresholdCalculator_hxx
#include "itkYenThresholdCalculator.h"
#include "itkProgressReporter.h"
#include "vnl/vnl_math.h"
namespace itk
{
/*
* Compute the Yen's threshold
*/
template<typename THistogram, typename TOutput>
void
YenThresholdCalculator<THistogram, TOutput>
::GenerateData(void)
{
const HistogramType * histogram = this->GetInput();
// histogram->Print(std::cout);
if ( histogram->GetTotalFrequency() == 0 )
{
itkExceptionMacro(<< "Histogram is empty");
}
ProgressReporter progress(this, 0, histogram->GetSize(0) );
if( histogram->GetSize(0) == 1 )
{
this->GetOutput()->Set( static_cast<OutputType>( histogram->GetMeasurement(0,0) ) );
}
unsigned int size = histogram->GetSize(0);
int threshold;
int ih, it;
double crit;
double max_crit;
std::vector<double> norm_histo(size); /* normalized histogram */
std::vector<double> P1(size); /* cumulative normalized histogram */
std::vector<double> P1_sq(size);
std::vector<double> P2_sq(size);
int total = histogram->GetTotalFrequency();
for (ih = 0; (unsigned)ih < size; ih++ )
{
norm_histo[ih] = (double)histogram->GetFrequency(ih, 0)/total;
}
P1[0]=norm_histo[0];
for (ih = 1; (unsigned)ih < size; ih++ )
{
P1[ih]= P1[ih-1] + norm_histo[ih];
}
P1_sq[0]=norm_histo[0]*norm_histo[0];
for (ih = 1; (unsigned)ih < size; ih++ )
{
P1_sq[ih]= P1_sq[ih-1] + norm_histo[ih] * norm_histo[ih];
}
P2_sq[size - 1] = 0.0;
for ( ih = (unsigned)size-2; ih >= 0; ih-- )
{
P2_sq[ih] = P2_sq[ih + 1] + norm_histo[ih + 1] * norm_histo[ih + 1];
}
/* Find the threshold that maximizes the criterion */
threshold = -1;
max_crit = itk::NumericTraits<double>::NonpositiveMin();
for ( it = 0; (unsigned)it < size; it++ )
{
crit = -1.0 * (( P1_sq[it] * P2_sq[it] )> 0.0? vcl_log( P1_sq[it] * P2_sq[it]):0.0) + 2 * ( ( P1[it] * ( 1.0 - P1[it] ) )>0.0? vcl_log( P1[it] * ( 1.0 - P1[it] ) ): 0.0);
if ( crit > max_crit )
{
max_crit = crit;
threshold = it;
}
}
this->GetOutput()->Set( static_cast<OutputType>( histogram->GetMeasurement( threshold, 0 ) ) );
}
} // end namespace itk
#endif
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