/// <summary>
/// Calculates the mean squared error of this and another DeblurFactor
/// </summary>
/// <param name="deblurFilter"></param>
/// <returns></returns>
public Complex GetMse(DeblurFilter deblurFilter)
{
double errorRe = 0;
double errorIm = 0;
//var r1 = Data.Channel1;
//var g1 = Data.Channel2;
//var b1 = Data.Channel3;
//var r2 = blurFactor.Data.Channel1;
//var g2 = blurFactor.Data.Channel2;
//var b2 = blurFactor.Data.Channel3;
//var ilength = r1.Width;
//var jlength = r1.Width;
Action <Complex, Complex, int, int> action = delegate(Complex c1, Complex c2, int i, int j) {
var divRe = c2.Real - c1.Real;
var divIm = c2.Imaginary - c1.Imaginary;
errorRe += divRe * divRe;
errorIm += divIm * divRe;
};
C0.FoldWith(deblurFilter.C0, action);
C1.FoldWith(deblurFilter.C1, action);
C2.FoldWith(deblurFilter.C2, action);
//for (var j = 0; j < jlength; j++)
// for (var i = 0; i < ilength; i++)
// {
// var divR = r2[i][j].Real - r1[i][j].Real;
// var divG = g2[i][j].Real - g1[i][j].Real;
// var divB = b2[i][j].Real - b1[i][j].Real;
// var divRi = r2[i][j].Imaginary - r1[i][j].Imaginary;
// var divGi = g2[i][j].Imaginary - g1[i][j].Imaginary;
// var divBi = b2[i][j].Imaginary - b1[i][j].Imaginary;
// errorRe += divR*divR;
// errorRe += divG*divG;
// errorRe += divB*divB;
// errorIm += divRi*divRi;
// errorIm += divGi*divGi;
// errorIm += divBi*divBi;
// }
return(new Complex(errorRe, errorIm));
}
/// <summary>
/// Creates a deblur filter from three channel in frequency domain.
/// </summary>
/// <param name="c0Freqz">channel 0 in frequency domain</param>
/// <param name="c1Freqz">channel 1 in frequency domain</param>
/// <param name="c2Freqz">channel 2 in frequency domain</param>
/// <param name="normalize">
/// if true, each pixel c_n with 0 < n < N-1 will be divided by 1/sum|c_n|, c_0 will be set
/// to 1+j0
/// </param>
/// <returns></returns>
public static DeblurFilter CreateFromFrequencies(Complex2D c0Freqz,
Complex2D c1Freqz,
Complex2D c2Freqz,
bool normalize = false)
{
var w = MathCV.Max(c0Freqz.Width, c1Freqz.Width, c2Freqz.Width);
var h = MathCV.Max(c0Freqz.Height, c1Freqz.Height, c2Freqz.Height);
var result = new DeblurFilter {
C0 = c0Freqz.Width != w || c0Freqz.Height != h?DoScale(c0Freqz, w, h) : new Complex2D(c0Freqz),
C1 = c1Freqz.Width != w || c1Freqz.Height != h?DoScale(c1Freqz, w, h) : new Complex2D(c1Freqz),
C2 = c2Freqz.Width != w || c2Freqz.Height != h?DoScale(c2Freqz, w, h) : new Complex2D(c2Freqz)
};
if (!normalize)
{
return(result);
}
var n = w * h;
var d0 = result.C0.Data;
var d1 = result.C1.Data;
var d2 = result.C2.Data;
var norm0 = (n - 1) / (d0.SumAbs() - d0[0].Magnitude);
var norm1 = (n - 1) / (d1.SumAbs() - d1[0].Magnitude);
var norm2 = (n - 1) / (d2.SumAbs() - d2[0].Magnitude);
d0[0] = d1[0] = d2[0] = Complex.One;
for (var i = 1; i < n; i++)
{
d0[i] *= norm0;
d1[i] *= norm1;
d2[i] *= norm2;
}
return(result);
}