public static int GetOtsuThreshold(MyImage img)
{
float[] d = new float[256];
int[] hist = new int[256];
d.Initialize();
int threshold;
long c1, c2, c12, m1, m2, diff;
GetHistogram(img, hist);
for (threshold = 1; threshold != 255; threshold++)
{
c1 = CalcCnt(1, threshold, hist);
c2 = CalcCnt(threshold + 1, 255, hist);
c12 = c1 * c2;
if (c12 == 0)
{
continue;
}
m1 = CalcMean(1, threshold, hist);
m2 = CalcMean(threshold + 1, 255, hist);
diff = m1 * c2 - m2 * c1;
d[threshold] = (float)diff * diff / c12;
}
threshold = FindMax(d);
return(threshold);
}
private static void GetHistogram(MyImage image, int[] hist)
{
hist.Initialize();
Parallel.For(0, image.Height, i =>
{
Parallel.For(0, image.Width, j =>
{
hist[(int)image.red[i, j]]++;
});
});
}
public static MyImage Convert(MyImage source)
{
Parallel.For(0, source.Height, i =>
{
Parallel.For(0, source.Width, j =>
{
var res = 0.21 * source.red[i, j] + 0.72 * source.green[i, j] + 0.07 * source.blue[i, j];
source.SetValue(i, j, res);
});
});
return(source);
}
public static MyImage Convert(MyImage source)
{
var th = GetOtsuThreshold(source);
var width = source.Width;
var height = source.Height;
Parallel.For(0, source.Height, i =>
{
Parallel.For(0, source.Width, j =>
{
var value = source.red[i, j] > th ? 255 : 0;
source.SetValue(i, j, value);
});
});
return(source);
}
public static MyImage FromArray(double[] points, int height, int width, List <int> pointIndexsToKeep)
{
var a = new HashSet <int>(pointIndexsToKeep);
var res = new MyImage(height, width);
var c = 0;
for (var i = 0; i < height; i++)
{
for (int j = 0; j < width; j++)
{
if (a.Contains(c))
{
res.blue[i, j] = points[c];
}
c += 1;
}
}
return(res);
}
