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/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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 itkCorrelationCoefficientHistogramImageToImageMetric_hxx
#define itkCorrelationCoefficientHistogramImageToImageMetric_hxx
namespace itk
{
template <typename TFixedImage, typename TMovingImage>
auto
CorrelationCoefficientHistogramImageToImageMetric<TFixedImage, TMovingImage>::EvaluateMeasure(
HistogramType & histogram) const -> MeasureType
{
const MeasureType varianceX = this->VarianceX(histogram);
const MeasureType varianceY = this->VarianceY(histogram);
const MeasureType covariance = this->Covariance(histogram);
return itk::Math::abs(covariance / (std::sqrt(varianceX) * std::sqrt(varianceY)));
}
template <typename TFixedImage, typename TMovingImage>
auto
CorrelationCoefficientHistogramImageToImageMetric<TFixedImage, TMovingImage>::MeanX(HistogramType & histogram) const
-> MeasureType
{
MeasureType meanX{};
for (unsigned int i = 0; i < this->m_HistogramSize[0]; ++i)
{
MeasureType valX = histogram.GetMeasurement(i, 0);
HistogramFrequencyType freq = histogram.GetFrequency(i, 0);
meanX += valX * freq;
}
meanX /= histogram.GetTotalFrequency();
return meanX;
}
template <typename TFixedImage, typename TMovingImage>
auto
CorrelationCoefficientHistogramImageToImageMetric<TFixedImage, TMovingImage>::MeanY(HistogramType & histogram) const
-> MeasureType
{
MeasureType meanY{};
for (unsigned int i = 0; i < this->m_HistogramSize[1]; ++i)
{
MeasureType valY = histogram.GetMeasurement(i, 1);
HistogramFrequencyType freq = histogram.GetFrequency(i, 1);
meanY += valY * freq;
}
meanY /= histogram.GetTotalFrequency();
return meanY;
}
template <typename TFixedImage, typename TMovingImage>
auto
CorrelationCoefficientHistogramImageToImageMetric<TFixedImage, TMovingImage>::VarianceX(HistogramType & histogram) const
-> MeasureType
{
MeasureType varX{};
for (unsigned int i = 0; i < this->m_HistogramSize[0]; ++i)
{
varX += static_cast<double>(histogram.GetFrequency(i, 0)) / histogram.GetTotalFrequency() *
std::pow(histogram.GetMeasurement(i, 0), 2);
}
return varX - std::pow(MeanX(histogram), 2);
}
template <typename TFixedImage, typename TMovingImage>
auto
CorrelationCoefficientHistogramImageToImageMetric<TFixedImage, TMovingImage>::VarianceY(HistogramType & histogram) const
-> MeasureType
{
MeasureType varY{};
for (unsigned int i = 0; i < this->m_HistogramSize[1]; ++i)
{
varY += static_cast<double>(histogram.GetFrequency(i, 1)) / histogram.GetTotalFrequency() *
std::pow(histogram.GetMeasurement(i, 1), 2);
}
return varY - std::pow(MeanY(histogram), 2);
}
template <typename TFixedImage, typename TMovingImage>
auto
CorrelationCoefficientHistogramImageToImageMetric<TFixedImage, TMovingImage>::Covariance(
HistogramType & histogram) const -> MeasureType
{
MeasureType var{};
MeasureType meanX = MeanX(histogram);
MeasureType meanY = MeanY(histogram);
for (unsigned int j = 0; j < this->m_HistogramSize[1]; ++j)
{
for (unsigned int i = 0; i < this->m_HistogramSize[0]; ++i)
{
typename HistogramType::IndexType index;
index.SetSize(2);
index[0] = i;
index[1] = j;
var += histogram.GetFrequency(index) * (histogram.GetMeasurement(i, 0) - meanX) *
(histogram.GetMeasurement(j, 1) - meanY);
}
}
var /= histogram.GetTotalFrequency();
return var;
}
} // namespace itk
#endif // itkCorrelationCoefficientHistogramImageToImageMetric_hxx
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