public static Bitmap LaplaceGreyscale(Bitmap b)
{
ImagerBitmap i = new ImagerBitmap(b.Clone() as Bitmap);
ImagerBitmap i2 = new ImagerBitmap(b.Clone() as Bitmap);
for (int column = 1; column < i.Bitmap.Width - 1; column++)
{
for (int row = 1; row < i.Bitmap.Height - 1; row++)
{
int[,] c = i.GetGrey3x3(row, column);
int val = (((c[0, 0] + c[0, 1] + c[0, 2] + c[1, 0] + c[1, 2] + c[2, 0] + c[2, 1]
+ c[2, 2]) * -1) + (c[1, 1] * 8)) + 128;
if (val >= 128)
{
val = 0;
}
else
{
val = 255;
}
i2.SetPixel(column, row, Color.FromArgb(val, val, val));
}
}
i.UnlockBitmap();
i2.UnlockBitmap();
return(i2.Bitmap.Clone() as Bitmap);
}
/// <summary>
/// Perform a Median fiter using a 5x5 Mask
/// </summary>
/// <param name="b">Image to Process</param>
/// <returns>Filtered Image</returns>
public static Bitmap Median5x5(Bitmap b)
{
ImagerBitmap i = new ImagerBitmap(b.Clone() as Bitmap);
ImagerBitmap i2 = new ImagerBitmap(b.Clone() as Bitmap);
for (int column = 2; column < i.Bitmap.Width - 2; column++)
{
for (int row = 2; row < i.Bitmap.Height - 2; row++)
{
Color[,] c = i.Get5x5(row, column);
int red = Median(c[0, 0].R, c[0, 1].R, c[0, 2].R, c[0, 3].R, c[0, 4].R, c[1, 0].R,
c[1, 1].R, c[1, 2].R, c[1, 3].R, c[1, 4].R, c[2, 0].R, c[2, 1].R, c[2, 2].R,
c[2, 3].R, c[2, 4].R, c[3, 0].R, c[3, 1].R, c[3, 2].R, c[3, 3].R, c[3, 4].R,
c[4, 0].R, c[4, 1].R, c[4, 2].R, c[4, 3].R, c[4, 4].R);
int green = Median(c[0, 0].G, c[0, 1].G, c[0, 2].G, c[0, 3].G, c[0, 4].G, c[1, 0].G,
c[1, 1].G, c[1, 2].G, c[1, 3].G, c[1, 4].G, c[2, 0].G, c[2, 1].G, c[2, 2].G,
c[2, 3].G, c[2, 4].G, c[3, 0].G, c[3, 1].G, c[3, 2].G, c[3, 3].G, c[3, 4].G,
c[4, 0].G, c[4, 1].G, c[4, 2].G, c[4, 3].G, c[4, 4].G);
int blue = Median(c[0, 0].B, c[0, 1].B, c[0, 2].B, c[0, 3].B, c[0, 4].B, c[1, 0].B,
c[1, 1].B, c[1, 2].B, c[1, 3].B, c[1, 4].B, c[2, 0].B, c[2, 1].B, c[2, 2].B,
c[2, 3].B, c[2, 4].B, c[3, 0].B, c[3, 1].B, c[3, 2].B, c[3, 3].B, c[3, 4].B,
c[4, 0].B, c[4, 1].B, c[4, 2].B, c[4, 3].B, c[4, 4].B);
i2.SetPixel(column, row, Color.FromArgb(red, green, blue));
}
}
i.UnlockBitmap();
i2.UnlockBitmap();
return(i2.Bitmap.Clone() as Bitmap);
}
/// <summary>
/// Perform a Bionomial filter using a 3x3 Mask
/// </summary>
/// <param name="b">Image to Process</param>
/// <returns>Filtered Image</returns>
public static Bitmap Binomial3x3(Bitmap b)
{
ImagerBitmap i = new ImagerBitmap(b.Clone() as Bitmap);
ImagerBitmap i2 = new ImagerBitmap(b.Clone() as Bitmap);
for (int column = 1; column < i.Bitmap.Width - 1; column++)
{
for (int row = 1; row < i.Bitmap.Height - 1; row++)
{
Color[,] c = i.Get3x3(row, column);
int red = ((c[0, 0].R * 1) + (c[0, 1].R * 2) + (c[0, 2].R * 1) + (c[1, 0].R * 2)
+ (c[1, 1].R * 4) + (c[1, 2].R * 2) + (c[2, 0].R * 1) + (c[2, 1].R * 2)
+ (c[2, 2].R * 1)) / 16;
int green = ((c[0, 0].G * 1) + (c[0, 1].G * 2) + (c[0, 2].G * 1) + (c[1, 0].G * 2)
+ (c[1, 1].G * 4) + (c[1, 2].G * 2) + (c[2, 0].G * 1) + (c[2, 1].G * 2)
+ (c[2, 2].G * 1)) / 16;
int blue = ((c[0, 0].B * 1) + (c[0, 1].B * 2) + (c[0, 2].B * 1) + (c[1, 0].B * 2)
+ (c[1, 1].B * 4) + (c[1, 2].B * 2) + (c[2, 0].B * 1) + (c[2, 1].B * 2)
+ (c[2, 2].B * 1)) / 16;
i2.SetPixel(column, row, Color.FromArgb(red, green, blue));
}
}
i.UnlockBitmap();
i2.UnlockBitmap();
return(i2.Bitmap.Clone() as Bitmap);
}
/// <summary>
/// Get the green pixels from the image
/// </summary>
/// <param name="b">Image to Process</param>
/// <returns>Filtered Image</returns>
public static Bitmap GetGreenBitmap(Bitmap b)
{
ImagerBitmap i = new ImagerBitmap(b.Clone() as Bitmap);
for (int column = 0; column < i.Bitmap.Width; column++)
{
for (int row = 0; row < i.Bitmap.Height; row++)
{
i.SetPixel(column, row, Color.FromArgb(0, i.GetPixel(column, row).G, 0));
}
}
i.UnlockBitmap();
return(i.Bitmap.Clone() as Bitmap);
}
/// <summary>
/// Perform laplace edge detection on the image
/// </summary>
/// <param name="b">Source Image</param>
/// <returns>Edges</returns>
public static Bitmap Laplace(Bitmap b)
{
ImagerBitmap i = new ImagerBitmap(b.Clone() as Bitmap);
ImagerBitmap i2 = new ImagerBitmap(b.Clone() as Bitmap);
for (int column = 1; column < i.Bitmap.Width - 1; column++)
{
for (int row = 1; row < i.Bitmap.Height - 1; row++)
{
Color[,] c = i.Get3x3(row, column);
int red = (((c[0, 0].R + c[0, 1].R + c[0, 2].R + c[1, 0].R + c[1, 2].R + c[2, 0].R
+ c[2, 1].R + c[2, 2].R) * -1) + (c[1, 1].R * 8)) + 128;
int green = (((c[0, 0].G + c[0, 1].G + c[0, 2].G + c[1, 0].G + c[1, 2].G
+ c[2, 0].G + c[2, 1].G + c[2, 2].G) * -1) + (c[1, 1].G * 8)) + 128;
int blue = (((c[0, 0].B + c[0, 1].B + c[0, 2].B + c[1, 0].B + c[1, 2].B + c[2, 0].B
+ c[2, 1].B + c[2, 2].B) * -1) + (c[1, 1].B * 8)) + 128;
if (red >= 128)
{
red = 0;
}
else
{
red = 255;
}
if (green >= 128)
{
green = 0;
}
else
{
green = 255;
}
if (blue >= 128)
{
blue = 0;
}
else
{
blue = 255;
}
i2.SetPixel(column, row, Color.FromArgb(red, green, blue));
}
}
i.UnlockBitmap();
i2.UnlockBitmap();
return(i2.Bitmap.Clone() as Bitmap);
}
public static Bitmap GetBlackAndWhiteBitmap2(Bitmap b)
{
ImagerBitmap i = new ImagerBitmap(b.Clone() as Bitmap);
double[] histogram = new double[256];
for (int column = 0; column < i.Bitmap.Width; column++)
{
for (int row = 0; row < i.Bitmap.Height; row++)
{
histogram[i.GetGreyPixel(column, row)]++;
}
}
double k = b.Width * b.Height;
double half = k / 2;
int middle = 0;
while (k > half)
{
k = k - histogram[middle];
middle++;
}
for (int column = 0; column < i.Bitmap.Width; column++)
{
for (int row = 0; row < i.Bitmap.Height; row++)
{
int val = (i.GetPixel(column, row).R + i.GetPixel(column, row).G
+ i.GetPixel(column, row).B) / 3;
if (val > middle)
{
val = 255;
}
else
{
val = 0;
}
i.SetPixel(column, row, Color.FromArgb(val, val, val));
}
}
i.UnlockBitmap();
return(i.Bitmap.Clone() as Bitmap);
}
/// <summary>
/// Perform a Binomial filter using a 5x5 Mask
/// </summary>
/// <param name="b">Image to Process</param>
/// <returns>Filtered Image</returns>
public static Bitmap Binomial5x5(Bitmap b)
{
ImagerBitmap i = new ImagerBitmap(b.Clone() as Bitmap);
ImagerBitmap i2 = new ImagerBitmap(b.Clone() as Bitmap);
for (int column = 2; column < i.Bitmap.Width - 2; column++)
{
for (int row = 2; row < i.Bitmap.Height - 2; row++)
{
Color[,] c = i.Get5x5(row, column);
int red = ((c[0, 0].R * 1) + (c[0, 1].R * 4) + (c[0, 2].R * 6) + (c[0, 3].R * 4)
+ (c[0, 4].R * 1) + (c[1, 0].R * 4) + (c[1, 1].R * 16) + (c[1, 2].R * 24)
+ (c[1, 3].R * 16) + (c[1, 4].R * 4) + (c[2, 0].R * 6) + (c[2, 1].R * 24)
+ (c[2, 2].R * 36) + (c[2, 3].R * 24) + (c[2, 4].R * 6) + (c[3, 0].R * 4)
+ (c[3, 1].R * 16) + (c[3, 2].R * 24) + (c[3, 3].R * 16) + (c[3, 4].R * 4)
+ (c[4, 0].R * 1) + (c[4, 1].R * 4) + (c[4, 2].R * 6) + (c[4, 3].R * 4)
+ (c[4, 4].R * 1)) / 256;
int green = ((c[0, 0].G * 1) + (c[0, 1].G * 4) + (c[0, 2].G * 6) + (c[0, 3].G * 4)
+ (c[0, 4].G * 1) + (c[1, 0].G * 4) + (c[1, 1].G * 16) + (c[1, 2].G * 24)
+ (c[1, 3].G * 16) + (c[1, 4].G * 4) + (c[2, 0].G * 6) + (c[2, 1].G * 24)
+ (c[2, 2].G * 36) + (c[2, 3].G * 24) + (c[2, 4].G * 6) + (c[3, 0].G * 4)
+ (c[3, 1].G * 16) + (c[3, 2].G * 24) + (c[3, 3].G * 16) + (c[3, 4].G * 4)
+ (c[4, 0].G * 1) + (c[4, 1].G * 4) + (c[4, 2].G * 6) + (c[4, 3].G * 4)
+ (c[4, 4].G * 1)) / 256;
int blue = ((c[0, 0].B * 1) + (c[0, 1].B * 4) + (c[0, 2].B * 6) + (c[0, 3].B * 4)
+ (c[0, 4].B * 1) + (c[1, 0].B * 4) + (c[1, 1].B * 16) + (c[1, 2].B * 24)
+ (c[1, 3].B * 16) + (c[1, 4].B * 4) + (c[2, 0].B * 6) + (c[2, 1].B * 24)
+ (c[2, 2].B * 36) + (c[2, 3].B * 24) + (c[2, 4].B * 6) + (c[3, 0].B * 4)
+ (c[3, 1].B * 16) + (c[3, 2].B * 24) + (c[3, 3].B * 16) + (c[3, 4].B * 4)
+ (c[4, 0].B * 1) + (c[4, 1].B * 4) + (c[4, 2].B * 6) + (c[4, 3].B * 4)
+ (c[4, 4].B * 1)) / 256;
i2.SetPixel(column, row, Color.FromArgb(red, green, blue));
}
}
i.UnlockBitmap();
i2.UnlockBitmap();
return(i2.Bitmap.Clone() as Bitmap);
}
/// <summary>
/// Make the image black and white
/// </summary>
/// <param name="b">Image to Process</param>
/// <returns>Filtered Image</returns>
public static Bitmap GetBlackAndWhiteBitmap(Bitmap b)
{
ImagerBitmap i = new ImagerBitmap(b.Clone() as Bitmap);
double[] histogram = new double[256];
for (int column = 0; column < i.Bitmap.Width; column++)
{
for (int row = 0; row < i.Bitmap.Height; row++)
{
histogram[i.GetGreyPixel(column, row)]++;
}
}
//find the position of the max value on the left
int leftK = 0;
for (int k = 0; k < 128; k++)
{
if (histogram[k] > histogram[leftK])
{
leftK = k;
}
}
//find the position of the max value on the right
int rightK = 0;
for (int k = 128; k < 256; k++)
{
if (histogram[k] > histogram[rightK])
{
rightK = k;
}
}
//find the min value between the 2 local maxes
int localMin = rightK;
for (int k = leftK; k < rightK; k++)
{
if (histogram[k] < histogram[localMin])
{
localMin = k;
}
}
for (int column = 0; column < i.Bitmap.Width; column++)
{
for (int row = 0; row < i.Bitmap.Height; row++)
{
int val = (i.GetPixel(column, row).R + i.GetPixel(column, row).G
+ i.GetPixel(column, row).B) / 3;
if (val > localMin)
{
val = 255;
}
else
{
val = 0;
}
i.SetPixel(column, row, Color.FromArgb(val, val, val));
}
}
i.UnlockBitmap();
return(i.Bitmap.Clone() as Bitmap);
}
/// <summary>
/// Subtract b2 from b1 and normalize the image
/// </summary>
/// <param name="b1">Image</param>
/// <param name="b2">Image</param>
/// <returns>Normalized Image</returns>
public static Bitmap Subtract(Bitmap b1, Bitmap b2)
{
if (b1.Width != b2.Width || b1.Height != b2.Height)
{
throw new Exception("Images not the same size cannot subtract");
}
ImagerBitmap i = new ImagerBitmap(b1.Clone() as Bitmap);
ImagerBitmap i2 = new ImagerBitmap(b2.Clone() as Bitmap);
int[,] red = new int[i.Bitmap.Width, i.Bitmap.Height];
int[,] blue = new int[i.Bitmap.Width, i.Bitmap.Height];
int[,] green = new int[i.Bitmap.Width, i.Bitmap.Height];
int redMax = 0;
int redMin = 0;
int redRange = 0;
int blueMax = 0;
int blueMin = 0;
int blueRange = 0;
int greenMax = 0;
int greenMin = 0;
int greenRange = 0;
//fill the arrays with the subtracted values
//Keep track of the min and max values for later
for (int column = 0; column < i.Bitmap.Width; column++)
{
for (int row = 0; row < i.Bitmap.Height; row++)
{
Color c1 = i.GetPixel(column, row);
Color c2 = i2.GetPixel(column, row);
red[column, row] = c2.R - c1.R;
blue[column, row] = c2.B - c1.B;
green[column, row] = c2.G - c1.G;
if (red[column, row] > redMax)
{
redMax = red[column, row];
}
if (red[column, row] < redMin)
{
redMin = red[column, row];
}
if (blue[column, row] > blueMax)
{
blueMax = blue[column, row];
}
if (blue[column, row] < blueMin)
{
blueMin = blue[column, row];
}
if (green[column, row] > greenMax)
{
greenMax = green[column, row];
}
if (green[column, row] < greenMin)
{
greenMin = green[column, row];
}
}
}
//find the range of the min an max
redRange = Math.Abs(redMax - redMin);
blueRange = Math.Abs(blueMax - blueMin);
greenRange = Math.Abs(greenRange - greenMin);
//Normalize the values in the arrays and load the result image
for (int column = 0; column < i.Bitmap.Width; column++)
{
for (int row = 0; row < i.Bitmap.Height; row++)
{
if (redRange != 0)
{
red[column, row] = 255 - (((redMax - red[column, row]) * 255) / redRange);
}
if (blueRange != 0)
{
blue[column, row] = 255 - (((blueMax - blue[column, row]) * 255) / blueRange);
}
if (greenRange != 0)
{
green[column, row] = 255 - (((greenMax - green[column, row]) * 255) / greenRange);
}
if (red[column, row] < 0)
{
red[column, row] = 0;
}
if (blue[column, row] < 0)
{
blue[column, row] = 0;
}
if (green[column, row] < 0)
{
green[column, row] = 0;
}
i2.SetPixel(column, row, Color.FromArgb(red[column, row], green[column, row],
blue[column, row]));
}
}
i.UnlockBitmap();
i2.UnlockBitmap();
return(i2.Bitmap.Clone() as Bitmap);
}