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308 | /* ============================================================
*
* This file is a part of digiKam project
* https://www.digikam.org
*
* Date : 28/08/2021
* Description : Image Quality Parser - Noise basic factor detection
*
* SPDX-FileCopyrightText: 2021-2025 by Gilles Caulier <caulier dot gilles at gmail dot com>
* SPDX-FileCopyrightText: 2021-2022 by Phuoc Khanh Le <phuockhanhnk94 at gmail dot com>
*
* References : https://cse.buffalo.edu/~siweilyu/papers/ijcv14.pdf
*
* SPDX-License-Identifier: GPL-2.0-or-later
*
* ============================================================ */
#include "noise_detector.h"
// Qt includes
#include <QtMath>
// Local includes
#include "digikam_debug.h"
namespace Digikam
{
const int SIZE_FILTER = 4;
NoiseDetector::Mat3D initFiltersHaar()
{
try
{
NoiseDetector::Mat3D res;
res.reserve(SIZE_FILTER * SIZE_FILTER);
float mat_base[SIZE_FILTER][SIZE_FILTER] =
{
{ 0.5F, 0.5F, 0.5F, 0.5F },
{ 0.5F, 0.5F, -0.5F, -0.5F },
{ 0.7071F, -0.7071F, 0.0F, 0.0F },
{ 0.0F, 0.0F, 0.7071F, -0.7071F }
};
cv::Mat mat_base_opencv = cv::Mat(SIZE_FILTER, SIZE_FILTER, CV_32FC1, &mat_base);
for (int i = 0 ; i < SIZE_FILTER ; i++)
{
for (int j = 0 ; j < SIZE_FILTER ; j++)
{
res.push_back(mat_base_opencv.row(i).t() * mat_base_opencv.row(j));
}
}
return res;
}
catch (cv::Exception& e)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "cv::Exception:" << e.what();
}
catch (...)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "Default exception from OpenCV";
}
return NoiseDetector::Mat3D();
}
const NoiseDetector::Mat3D NoiseDetector::filtersHaar = initFiltersHaar();
class Q_DECL_HIDDEN NoiseDetector::Private
{
public:
Private() = default;
int size_filter = 4;
float alpha = 18.0F;
float beta = 7.0F;
};
// Main noise detection
NoiseDetector::NoiseDetector()
: AbstractDetector(),
d (new Private)
{
}
NoiseDetector::~NoiseDetector()
{
delete d;
}
float NoiseDetector::detect(const cv::Mat& image) const
{
try
{
cv::Mat image_float = image;
image_float.convertTo(image_float, CV_32F);
// Decompose to channels
Mat3D channels = decompose_by_filter(image_float, filtersHaar);
// Calculate variance and kurtosis
cv::Mat variance, kurtosis;
calculate_variance_kurtosis(channels, variance, kurtosis);
// Calculate variance of noise
float V = noise_variance(variance, kurtosis);
return normalize(V);
}
catch (cv::Exception& e)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "cv::Exception:" << e.what();
}
catch (...)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "Default exception from OpenCV";
}
return 1.0F;
}
NoiseDetector::Mat3D NoiseDetector::decompose_by_filter(const cv::Mat& image, const Mat3D& filters) const
{
try
{
Mat3D filtersUsed = filters.mid(1); // do not use first filter
Mat3D channels;
channels.reserve(filtersUsed.size());
for (const auto& filter : std::as_const(filtersUsed))
{
cv::Mat tmp = cv::Mat(image.size().width, image.size().height, CV_32FC1);
cv::filter2D(image, tmp, -1, filter, cv::Point(-1, -1), 0.0, cv::BORDER_REPLICATE);
channels.push_back(tmp);
}
return channels;
}
catch (cv::Exception& e)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "cv::Exception:" << e.what();
}
catch (...)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "Default exception from OpenCV";
}
return Mat3D();
}
void NoiseDetector::calculate_variance_kurtosis(const Mat3D& channels, cv::Mat& variance, cv::Mat& kurtosis) const
{
try
{
// Get raw moments
cv::Mat mu1 = raw_moment(channels, 1);
cv::Mat mu2 = raw_moment(channels, 2);
cv::Mat mu3 = raw_moment(channels, 3);
cv::Mat mu4 = raw_moment(channels, 4);
// Calculate variance and kurtosis projection
variance = mu2 - pow_mat(mu1, 2);
kurtosis = (mu4 - 4.0 * mu1.mul(mu3) + 6.0 * pow_mat(mu1,2).mul(mu2) - 3.0 * pow_mat(mu1,4)) / pow_mat(variance, 2) - 3.0;
cv::threshold(kurtosis, kurtosis, 0, 0, cv::THRESH_TOZERO);
}
catch (cv::Exception& e)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "cv::Exception:" << e.what();
}
catch (...)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "Default exception from OpenCV";
}
}
float NoiseDetector::noise_variance(const cv::Mat& variance, const cv::Mat& kurtosis) const
{
try
{
cv::Mat sqrt_kurtosis;
cv::sqrt(kurtosis, sqrt_kurtosis);
float aa = mean_mat(sqrt_kurtosis);
float bb = mean_mat(pow_mat(variance, -1));
float cc = mean_mat(pow_mat(variance, -2));
float dd = mean_mat(sqrt_kurtosis.mul(pow_mat(variance, -1)));
float sqrtK = (aa*cc - bb*dd) / (cc-bb * bb);
return ((1.0F - aa / sqrtK) / bb);
}
catch (cv::Exception& e)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "cv::Exception:" << e.what();
}
catch (...)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "Default exception from OpenCV";
}
return 1.0F;
}
cv::Mat NoiseDetector::raw_moment(const NoiseDetector::Mat3D& mat, int order) const
{
try
{
float taille_image = mat[0].size().width * mat[0].size().height;
std::vector<float> vec;
vec.reserve(mat.size());
for (const auto& mat2d : std::as_const(mat))
{
vec.push_back(cv::sum(pow_mat(mat2d, order))[0] / taille_image);<--- Consider using std::transform algorithm instead of a raw loop.
}
return cv::Mat(vec, true);
}
catch (cv::Exception& e)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "cv::Exception:" << e.what();
}
catch (...)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "Default exception from OpenCV";
}
return cv::Mat();
}
cv::Mat NoiseDetector::pow_mat(const cv::Mat& mat, float order) const
{
try
{
cv::Mat res = cv::Mat(mat.size().width, mat.size().height, CV_32FC1);
cv::pow(mat, order, res);
return res;
}
catch (cv::Exception& e)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "cv::Exception:" << e.what();
}
catch (...)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "Default exception from OpenCV";
}
return cv::Mat();
}
float NoiseDetector::mean_mat(const cv::Mat& mat) const
{
try
{
cv::Scalar mean, std;
cv::meanStdDev(mat,mean,std);
return mean[0];
}
catch (cv::Exception& e)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "cv::Exception:" << e.what();
}
catch (...)
{
qCCritical(DIGIKAM_FACESENGINE_LOG) << "Default exception from OpenCV";
}
return 1.0F;
}
/**
* Normalize result to interval [0 - 1]
*/
float NoiseDetector::normalize(const float number) const
{
return (1.0F / (1.0F + qExp(-(number - d->alpha) / d->beta)));
}
} // namespace Digikam
#include "moc_noise_detector.cpp"
|