//double L, u, v;
public Quantize()
{
for (int i = 0; i < 160; i++)
{
LuvIndex[i] = new LUVClass();
}
}
public void createMatrix()
{
int N = 159;
similarityMatrix = new double[N, N];
Quantize q = new Quantize();
for (int index1 = 0; index1 < N; index1++)
{
for (int index2 = 0; index2 < N; index2++)
{
LUVClass luv1 = q.getLUVfromIndex(index1);
LUVClass luv2 = q.getLUVfromIndex(index2);
double distance = getEuclideanDistance(luv1, luv2);
if (distance > tColor)
{
similarityMatrix[index1, index2] = 0;
}
else
{
similarityMatrix[index1, index2] = 1 - distance / tColor;
}
}
}
//return similarityMatrix;
}
private LUVClass[,] getLuvMatrix(Bitmap img)
{
LUVClass[,] matrix = new LUVClass[img.Width, img.Height];
for (int i = 0; i < img.Width; i++)
{
for (int j = 0; j < img.Height; j++)
{
Color pixel = img.GetPixel(i, j);
var myRgb = new Rgb {
R = pixel.R, G = pixel.G, B = pixel.B
};
var myLuv = myRgb.To <Luv>();
matrix[i, j] = new LUVClass(myLuv.L, myLuv.U, myLuv.V);
}
}
return(matrix);
}
private void initializeMaxDistance()
{
int N = 159;
Quantize q = new Quantize();
double max = 0;
for (int index1 = 0; index1 < N; index1++)
{
for (int index2 = 0; index2 < N; index2++)
{
LUVClass luv1 = q.getLUVfromIndex(index1);
LUVClass luv2 = q.getLUVfromIndex(index2);
double distance = getEuclideanDistance(luv1, luv2);
if (distance > max)
{
max = distance;
}
}
}
dMax = max;
tColor = p * dMax;
}
private LUVClass[,] blurredMatrix(LUVClass[,] luv)
{
LUVClass[,] result = new LUVClass[width, height];
for (int i = 1; i < width - 1; i += 2)
{
for (int j = 1; j < height - 1; j += 2)
{
double aveL = 0.0;
double aveU = 0.0;
double aveV = 0.0;
aveL += luv[i - 1, j - 1].L + luv[i, j - 1].L + luv[i + 1, j - 1].L +
luv[i - 1, j].L + luv[i, j].L + luv[i + 1, j].L +
luv[i - 1, j + 1].L + luv[i, j + 1].L + luv[i + 1, j + 1].L;
aveU += luv[i - 1, j - 1].u + luv[i, j - 1].u + luv[i + 1, j - 1].u +
luv[i - 1, j].u + luv[i, j].u + luv[i + 1, j].u +
luv[i - 1, j + 1].u + luv[i, j + 1].u + luv[i + 1, j + 1].u;
aveV += luv[i - 1, j - 1].v + luv[i, j - 1].v + luv[i + 1, j - 1].v +
luv[i - 1, j].v + luv[i, j].v + luv[i + 1, j].v +
luv[i - 1, j + 1].v + luv[i, j + 1].v + luv[i + 1, j + 1].v;
aveL /= 9;
aveU /= 9;
aveV /= 9;
LUVClass myLuv = new LUVClass(aveL, aveU, aveV);
//Console.WriteLine("ij" + i + "," + j);
result[i - 1, j - 1] = myLuv; result[i, j - 1] = myLuv; result[i + 1, j - 1] = myLuv;
result[i - 1, j] = myLuv; result[i, j] = myLuv; result[i + 1, j] = myLuv;
result[i - 1, j + 1] = myLuv; result[i, j + 1] = myLuv; result[i + 1, j + 1] = myLuv;
}
}
if (width % 2 == 0)
{
int hei = height;
if (height % 2 == 0)
{
hei -= 1;
}
for (int i = 0; i < hei; i++)
{
result[width - 1, i] = result[width - 2, i];
}
}
if (height % 2 == 0)
{
for (int j = 0; j < width; j++)
{
result[j, height - 1] = result[j, height - 2];
}
if (width % 2 == 0)
{
result[width - 1, height - 1] = result[width - 1, height - 2];
}
}
//Console.WriteLine(result[125, 83]+ " "+ result[126, 83] + " " + result[127, 83]);
//Console.WriteLine(result[125, 84] + " " + result[126, 84] + " " + result[127, 84]);
return(result);
}
private double getEuclideanDistance(LUVClass l1, LUVClass l2)
{
double val = Math.Sqrt(Math.Pow(l1.L - l2.L, 2) + Math.Pow(l1.u - l2.u, 2) + Math.Pow(l1.v - l2.v, 2));
return(val);
}
