public TypicalImage custom_filter(float[,] filter, int width, int height, Postprocessing post)
{
FWidth = width;
FHeight = height;
return(LinearFilter(filter, FWidth / 2, FHeight / 2, post));
}
public TypicalImage LinearFilter(float[,] filter, int Origx, int Origy, Postprocessing post)
{
TypicalImage img = new TypicalImage(this);
TypicalImage edited_img = new TypicalImage(this);
int padWidth, padHeight;
double[] buffer = new double[width * height * 3];
int z = 0;
padWidth = Math.Max(FWidth - Origx, Origx);
padHeight = Math.Max(FHeight - Origy, Origy);
img.padding(padWidth, padHeight);
for (int y = padHeight; y < height + padHeight; y++)
{
for (int x = padWidth; x < width + padWidth; x++, z += 3)
{
float R = 0, G = 0, B = 0;
for (int i = 0; i < FWidth; i++)
{
for (int j = 0; j < FHeight; j++)
{
R += img.buffer2d[x - Origx + i, y - Origy + j].R * filter[i, j];
G += img.buffer2d[x - Origx + i, y - Origy + j].G * filter[i, j];
B += img.buffer2d[x - Origx + i, y - Origy + j].B * filter[i, j];
}
}
buffer[z] = R;
buffer[z + 1] = G;
buffer[z + 2] = B;
}
}
if (post == Postprocessing.Cut_off)
{
edited_img.cut_off(buffer);
}
else if (post == Postprocessing.No)
{
edited_img.no_postprocess(buffer);
}
else if (post == Postprocessing.Absolute)
{
edited_img.absolute(buffer);
}
else if (post == Postprocessing.Normalization)
{
edited_img.normalization(buffer, edited_img);
}
return(edited_img);
}
public TypicalImage LinearFilter(float[,] filter,int Origx, int Origy, Postprocessing post)
{
TypicalImage img = new TypicalImage(this);
TypicalImage edited_img = new TypicalImage(this);
int padWidth, padHeight;
double[] buffer = new double[width * height * 3];
int z = 0 ;
padWidth = Math.Max(FWidth - Origx, Origx);
padHeight = Math.Max(FHeight - Origy, Origy);
img.padding(padWidth, padHeight);
for (int y = padHeight; y < height + padHeight; y++)
{
for (int x = padWidth; x < width + padWidth; x++,z += 3)
{
float R = 0, G = 0, B = 0;
for (int i = 0; i < FWidth; i++)
{
for (int j = 0; j < FHeight; j++)
{
R += img.buffer2d[x - Origx + i, y - Origy + j].R * filter[i, j];
G += img.buffer2d[x - Origx + i, y - Origy + j].G * filter[i, j];
B += img.buffer2d[x - Origx + i, y - Origy + j].B * filter[i, j];
}
}
buffer[z] = R;
buffer[z + 1] = G;
buffer[z + 2] = B;
}
}
if (post == Postprocessing.Cut_off)
{
edited_img.cut_off(buffer);
}
else if (post == Postprocessing.No)
{
edited_img.no_postprocess(buffer);
}
else if (post == Postprocessing.Absolute)
{
edited_img.absolute(buffer);
}
else if (post == Postprocessing.Normalization)
{
edited_img.normalization(buffer, edited_img);
}
return edited_img;
}
public TypicalImage custom_filter(float[,] filter,int width,int height, Postprocessing post)
{
FWidth = width;
FHeight = height;
return LinearFilter(filter, FWidth / 2, FHeight / 2, post);
}
