public ImageProcessor GetFourierTransformedImages(double normalizationScale, double logoffset)
{
var realImage = new double[Image.Width, Image.Height];
var imaginaryImage = new double[Image.Width, Image.Height];
var signal = new Complex[Image.Width, Image.Height];
for (int i = 0; i < Image.Width; i++)
{
for (int j = 0; j < Image.Height; j++)
{
signal[i, j] = Image[i, j].R;
}
}
FourierTransformation.FFT2(signal, FourierTransformation.Direction.Forward);
var copy = new Complex[Image.Width, Image.Height];
ComplexToImages(copy, signal, realImage, imaginaryImage);
Normalize(realImage, normalizationScale, logoffset);
Normalize(imaginaryImage, normalizationScale, logoffset);
return(new ImageProcessor(CreateImage(realImage), CreateImage(imaginaryImage), copy));
}
public Image <Rgb24> ReverseFourierTransform()
{
var signal = new Complex[Image.Width, Image.Height];
var normalImage = new double[Image.Width, Image.Height];
for (int i = 0; i < Image.Width; i++)
{
for (int j = 0; j < Image.Height; j++)
{
signal[i, j] = TransformedSignal[i, j];
}
}
FourierTransformation.FFT2(signal, FourierTransformation.Direction.Backward);
for (int i = 0; i < Image.Width; i++)
{
for (int j = 0; j < Image.Height; j++)
{
normalImage[i, j] = signal[i, j].Real;
}
}
return(CreateImage(normalImage));
}
static void Main(string[] args)
{
List <DataModel> datas = new DataParser("asd.csv").LoadFromTextFile();
//asd123
using var sw = new StreamWriter("result.csv");
sw.WriteLine("No,Ido,Bemenet,Re,Im,Magnitude,dB,Phase");
foreach (var d in datas)
{
List <Complex> cmplx = new List <Complex>();
foreach (var item in d.RawData)
{
cmplx.Add(new Complex(item));
}
var result = new FourierTransformation().FastFourierTransformation(cmplx.Take(256).ToArray());
for (int i = 0; i < result.Length; i++)
{
sw.WriteLine($"{i},{d.RecordTime},{d.RawData[i]},{result[i].Real},{result[i].Imaginary},{result[i].Magnitude},{result[i].Decibell},{result[i].Phase}");
}
}
}
