pixel3f *Image::createEdges(float stylization)
{
pixel3f *gaussianE = createGaussian(SIGMA);
pixel3f *gaussianR = createGaussian(sqrtf(1.6) * SIGMA);
for (int i = 0; i < _width * _height; i++) {
// Difference of gaussians mapped to a smoothed step function.
float dog = gaussianE[i].L - TAU * gaussianR[i].L;
gaussianE[i].L = dog > 0.0f ? 100.0f : 100.0f * (1.0f + tanhf(stylization * dog));
}
delete[] gaussianR;
return gaussianE;
}
void MainWidgetTFM::filterFFT(){
for (int pulsing = 0; pulsing < numElements; pulsing++) {
if(pulsing % 10 == 0)
qDebug() << "filtering: " << ((float)pulsing) * 100.0/((float)numElements) << "%";
for (int element = 0; element < numElements; element++) {
// copy the array to fftw_complex structure, could be a faster way e.g. memcpy
for (int i = 0; i < sampleSize; i++) {
in[i][0] = m_data[index3d(i,element,pulsing)];
in[i][1] = 0;
}
//for (int i = 0; i < 100; i++) std::cout << i << ": " << in[i][0] << std::endl;
/* FFT */
fftw_plan my_plan = fftw_plan_dft_1d(sampleSize, in, out, FFTW_FORWARD, FFTW_ESTIMATE);
fftw_execute(my_plan);
for (int i = 0; i < sampleSize; i++) {
out[i][0] /= (float)sampleSize;
out[i][1] /= (float)sampleSize;
//std::cout << i << ": " << out[i][0] << " , " << out[i][1] << "i" << std::endl;
}
for (int i = 0; i < sampleSize; i++) {
//magnitude[i] = sqrt(out[i][0]*out[i][0] + out[i][1]*out[i][1]);
//std::cout << i << ": " << magnitude[i] << std::endl;
//outfile << to_string(magnitude[i]) << endl;
}
//int peak_frequency = 0;
//double peak_val = 0.0;
//for(int i = 0; i < 500; i++){
// //std::cout << i << ": " << magnitude[i] << std::endl;
// if(magnitude[i] > peak_val){
// std::cout << "new peak : " << i << std::endl;
// peak_val = magnitude[i];
// peak_frequency = i;
// }
//}
//std::cout << "peak_frequency(index) : " << peak_frequency << std::endl;
//float time_period = 1.0 / peak_frequency;
fftw_destroy_plan(my_plan);
/* FILTERING */
// Create gaussian filter vector
// f(x; sig, c) = e ^ ( -(x-c)^2 / 2*sig^2 )
//float sigma, c;
//createGaussian(70, 200);
createGaussian();
double weight = 2.0;
for (int i = 0; i < sampleSize; i++) {
out[i][0] = out[i][0] * gaussFilter[i] * weight;
out[i][1] = out[i][1] * gaussFilter[i] * weight;
}
for (int i = 500; i < sampleSize; i++) {
//out[i][0] = 0.0;
//out[i][1] = 0.0;
}
/* INVERSE FFT */
// To check that there's no existing data
for (int i = 0; i < sampleSize; i++) {
in[i][0] = 0;
in[i][1] = 0;
}
my_plan = fftw_plan_dft_1d(sampleSize, out, in, FFTW_BACKWARD, FFTW_ESTIMATE);
fftw_execute(my_plan);
//for (int i = 0; i < 100; i++) std::cout << i << ": " << in[i][0] << std::endl;
//for (int i = 0; i < sampleSize; i++) std::cout << i << ": " << in[i][0] << " , " << in[i][1] << "i" << std::endl;
fftw_destroy_plan(my_plan);
// multiply output by 2 (why?)
for (int i = 0; i < sampleSize; i++) {
in[i][0] *= 2.0;
in[i][1] *= 2.0;
//qDebug() << in[i][0];
//qDebug() << in[i][1];
}
// Calc absolute value and put back into array
for (int i = 0; i < sampleSize; i++) {
//m_filtered_data_ri[element][i][0] = (in[i][0]);//(float)
//m_filtered_data_ri[element][i][1] = (in[i][1]);//(float)
m_filtered_data_ri[index3d(i,element,pulsing)*2] = (in[i][0]);//(float)
m_filtered_data_ri[index3d(i,element,pulsing)*2+1] = (in[i][1]);//(float)
}
}
}
// calculate in seconds, using sampling rate
//time_period = time_period / samplingRate;
//std::cout << "test" << std::endl;
//float frequency = 1 / time_period;
//std::cout << "peak frequency : " << frequency << std::endl;
}
