/usr/include/ITK-4.12/itkMaximumEntropyThresholdCalculator.hxx is in libinsighttoolkit4-dev 4.12.2-dfsg1-1ubuntu1.
This file is owned by root:root, with mode 0o644.
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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 itkMaximumEntropyThresholdCalculator_hxx
#define itkMaximumEntropyThresholdCalculator_hxx
#include "itkMaximumEntropyThresholdCalculator.h"
#include "itkProgressReporter.h"
#include "itkMath.h"
namespace itk
{
template<typename THistogram, typename TOutput>
void
MaximumEntropyThresholdCalculator<THistogram, TOutput>
::GenerateData(void)
{
const HistogramType * histogram = this->GetInput();
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 = -1;
int ih, it;
int first_bin;
int last_bin;
double tot_ent; // total entropy
double max_ent; // max entropy
double ent_back; // entropy of the background pixels at a given threshold
double ent_obj; // entropy of the object pixels at a given threshold
std::vector<double> norm_histo(size); // normalized histogram
std::vector<double> P1(size); // cumulative normalized histogram
std::vector<double> P2(size);
const double tolerance = itk::NumericTraits<double>::epsilon();
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];
P2[0] = 1.0 - P1[0];
for( ih = 1; (unsigned)ih < size; ih++ )
{
P1[ih] = P1[ih-1] + norm_histo[ih];
P2[ih] = 1.0 - P1[ih];
}
// Determine the first non-zero bin
first_bin = 0;
for( ih = 0; (unsigned)ih < size; ih++ )
{
if ( !(std::abs(P1[ih]) < tolerance) )
{
first_bin = ih;
break;
}
}
// Determine the last non-zero bin
last_bin = size - 1;
for( ih = size - 1; ih >= first_bin; ih-- )
{
if ( !(std::abs(P2[ih]) < tolerance) )
{
last_bin = ih;
break;
}
}
// Calculate the total entropy each gray-level and find the threshold that
// maximizes it
max_ent = itk::NumericTraits<double>::min();
for ( it = first_bin; it <= last_bin; it++ )
{
// Entropy of the background pixels
ent_back = 0.0;
for ( ih = 0; ih <= it; ih++ )
{
if ( histogram->GetFrequency(ih, 0) != 0 )
{
ent_back -= ( norm_histo[ih] / P1[it] ) * std::log ( norm_histo[ih] / P1[it] );
}
}
// Entropy of the object pixels
ent_obj = 0.0;
for ( ih = it + 1; (unsigned)ih < size; ih++ )
{
if (histogram->GetFrequency(ih, 0) != 0)
{
ent_obj -= ( norm_histo[ih] / P2[it] ) * std::log ( norm_histo[ih] / P2[it] );
}
}
// Total entropy
tot_ent = ent_back + ent_obj;
// IJ.log(""+max_ent+" "+tot_ent);
const double tol = 0.00001;
if ( max_ent < (tot_ent - tol) )
{
max_ent = tot_ent;
threshold = it;
}
}
this->GetOutput()->Set( static_cast<OutputType>( histogram->GetMeasurement( threshold, 0 ) ) );
}
} // end namespace itk
#endif
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