static GrayscaleFloatImage RD(float[,] matr)
{
int h = matr.GetUpperBound(1) + 1;
int w = matr.GetUpperBound(0) + 1;
GrayscaleFloatImage tmp_img = new GrayscaleFloatImage(w, h);
float max_one = 0, min_one = 255;
for (int y = 0; y < h; ++y)
{
for (int x = 0; x < w; ++x)
{
max_one = Math.Max(max_one, matr[x, y]);
min_one = Math.Min(min_one, matr[x, y]);
}
}
for (int y = 0; y < h; ++y)
{
for (int x = 0; x < w; ++x)
{
/*if (matr[x, y] >= 2)
* tmp_img[x, y] = 255;
* else
* tmp_img[x, y] = 0;
*/
tmp_img[x, y] = (matr[x, y] - min_one) * 255 / (max_one - min_one);
}
}
return(tmp_img);
}
public static GrayscaleFloatImage Bilinear(GrayscaleFloatImage image, double n)
{
var width = (int)(image.Width * n);
var height = (int)(image.Height * n);
var result = new GrayscaleFloatImage(width, height);
//
for (var y = 0; y < height; y++)
{
var dy = y / n;
for (var x = 0; x < width; x++)
{
var dx = x / n;
if ((Math.Abs(dx % 1) <= 0) && (Math.Abs(dy % 1) <= 0))
{
result[x, y] = image[(int)dx, (int)dy];
}
else
{
var x1 = (int)dx;
var y1 = (int)dy;
result[x, y] = (float)((dy - y1) * ((x1 + 1 - dx) * image[x1, y1 + 1 >= image.Height ? image.Height - 1 : y1 + 1] +
(dx - x1) * image[x1 + 1 >= image.Width ? image.Width - 1 : x1 + 1, y1 + 1 >= image.Height ? image.Height - 1 : y1 + 1]) +
(y1 + 1 - dy) * ((x1 + 1 - dx) * image[x1, y1] +
(dx - x1) * image[x1 + 1 >= image.Width ? image.Width - 1 : x1 + 1, y1]));
}
}
}
return(result);
}
public static GrayscaleFloatImage Process(GrayscaleFloatImage Image, double SigmaD, double SigmaR)
{
var width = Image.Width;
var height = Image.Height;
var windowSize = 15;
var result = Image;
windowSize = windowSize % 2 == 0 ? windowSize - 1 : windowSize;
var n = (windowSize - 1) / 2;
for (var y = 0; y < height; y++)
for (var x = 0; x < width; x++)
{
double ch = 0;
double zn = 0;
for (var j = 0; j < windowSize; j++)
for (var i = 0; i < windowSize; i++)
{
var w = Math.Exp((-(i - n) * (i - n) - (j - n) * (j - n)) / (2 * SigmaD * SigmaD) - (Image[x, y] -
Image[x + i - n < 0 ? 0 : x + i - n >= width ? width - 1 : x + i - n, y + j - n < 0 ? 0 : y + j - n >= height ? height - 1 : y + j - n]) * (Image[x, y] -
Image[x + i - n < 0 ? 0 : x + i - n >= width ? width - 1 : x + i - n, y + j - n < 0 ? 0 : y + j - n >= height ? height - 1 : y + j - n]) / (2 * SigmaR * SigmaR));
ch += Image[x + i - n <= 0 ? 0 : x + i - n >= width ? width - 1 : x + i - n, y + j - n < 0 ? 0 : y + j - n >= height ? height - 1 : y + j - n] * w;
zn += w;
}
result[x, y] = (float)(ch / zn);
}
return result;
}
public static GrayscaleFloatImage Vessels(GrayscaleFloatImage image, int size, double sigma)
{
var angle = 15;
var images = new GrayscaleFloatImage[6];
for (var i = 0; i < 6; i++)
{
images[i] = Gabor(image, Filters.Gabor(6, 2, 3, angle, 1, 0), 6, 6);
angle += 30;
}
var result = new GrayscaleFloatImage(image.Width, image.Height);
for (var y = 0; y < image.Height; y++)
{
for (var x = 0; x < image.Width; x++)
{
result[x, y] = 0;
for (var i = 0; i < 6; i++)
{
if (images[i][x, y] <
result[x, y])
{
result[x, y] = images[i][x, y];
}
}
result[x, y] = Math.Abs(result[x, y]);
}
}
return(result);
}
public static GrayscaleFloatImage Process(GrayscaleFloatImage image, float sigma, float th, float tl)
{
var canny = new Canny(image, sigma, th, tl);
var result = canny.Image;
return(result);
}
public static Bitmap ImageToBitmap(GrayscaleFloatImage image)
{
Bitmap B = new Bitmap(image.Width, image.Height, PixelFormat.Format24bppRgb);
LockBitmapInfo lbi = LockBitmap(B);
try
{
for (int j = 0; j < image.Height; j++)
{
for (int i = 0; i < image.Width; i++)
{
byte c = image[i, j] < 0.0f ? (byte)0 : image[i, j] > 255.0f ? (byte)255 : (byte)image[i, j];
lbi.data[lbi.linewidth * j + i * 4] = c;
lbi.data[lbi.linewidth * j + i * 4 + 1] = c;
lbi.data[lbi.linewidth * j + i * 4 + 2] = c;
}
}
}
finally
{
UnlockBitmap(lbi);
}
return(B);
}
public static GrayscaleFloatImage Process(GrayscaleFloatImage Image, double SigmaD, double SigmaR)
{
var width = Image.Width;
var height = Image.Height;
var windowSize = 15;
var result = Image;
windowSize = windowSize % 2 == 0 ? windowSize - 1 : windowSize;
var n = (windowSize - 1) / 2;
for (var y = 0; y < height; y++)
{
for (var x = 0; x < width; x++)
{
double ch = 0;
double zn = 0;
for (var j = 0; j < windowSize; j++)
{
for (var i = 0; i < windowSize; i++)
{
var w = Math.Exp((-(i - n) * (i - n) - (j - n) * (j - n)) / (2 * SigmaD * SigmaD) - (Image[x, y] -
Image[x + i - n < 0 ? 0 : x + i - n >= width ? width - 1 : x + i - n, y + j - n < 0 ? 0 : y + j - n >= height ? height - 1 : y + j - n]) * (Image[x, y] -
Image[x + i - n < 0 ? 0 : x + i - n >= width ? width - 1 : x + i - n, y + j - n < 0 ? 0 : y + j - n >= height ? height - 1 : y + j - n]) / (2 * SigmaR * SigmaR));
ch += Image[x + i - n <= 0 ? 0 : x + i - n >= width ? width - 1 : x + i - n, y + j - n < 0 ? 0 : y + j - n >= height ? height - 1 : y + j - n] * w;
zn += w;
}
}
result[x, y] = (float)(ch / zn);
}
}
return(result);
}
public static GrayscaleFloatImage Bilinear(GrayscaleFloatImage image, double n)
{
var width = (int)(image.Width * n);
var height = (int)(image.Height * n);
var result = new GrayscaleFloatImage(width, height);
//
for (var y = 0; y < height; y++)
{
var dy = y / n;
for (var x = 0; x < width; x++)
{
var dx = x / n;
if ((Math.Abs(dx % 1) <= 0) && (Math.Abs(dy % 1) <= 0))
{
result[x, y] = image[(int)dx, (int)dy];
}
else
{
var x1 = (int)dx;
var y1 = (int)dy;
result[x, y] = (float)((dy - y1) * ((x1 + 1 - dx) * image[x1, y1 + 1 >= image.Height ? image.Height - 1 : y1 + 1] +
(dx - x1) * image[x1 + 1 >= image.Width ? image.Width - 1 : x1 + 1, y1 + 1 >= image.Height ? image.Height - 1 : y1 + 1]) +
(y1 + 1 - dy) * ((x1 + 1 - dx) * image[x1, y1] +
(dx - x1) * image[x1 + 1 >= image.Width ? image.Width - 1 : x1 + 1, y1]));
}
}
}
return result;
}
static float[, ][,] matrix_der2(GrayscaleFloatImage image, float sigma)
{
float[, ][,] out_matr = new float[image.Width, image.Height][, ];
float[,] Gxx = g_kernel(sigma, "xx");
float[,] Gxy = g_kernel(sigma, "xy");
float[,] Gyy = g_kernel(sigma, "yy");
int rad = (int)Math.Round(3 * sigma);
GrayscaleFloatImage temp_image = img_expansion(image.ToColorFloatImage(), "odd", rad).ToGrayscaleFloatImage();
for (int y = rad; y < image.Height + rad; ++y)
{
for (int x = rad; x < image.Width + rad; ++x)
{
float[,] q = new float[2, 2];
for (int m = -rad; m <= rad; ++m)
{
for (int n = -rad; n <= rad; ++n)
{
q[0, 0] += temp_image[x + n, y + m] * Gxx[rad + n, rad + m];
q[0, 1] += temp_image[x + n, y + m] * Gxy[rad + n, rad + m];
q[1, 1] += temp_image[x + n, y + m] * Gyy[rad + n, rad + m];
}
}
q[1, 0] = q[0, 1];
out_matr[x - rad, y - rad] = q;
}
}
return(out_matr);
}
public static GrayscaleFloatImage MedianFilter(GrayscaleFloatImage image, int kernelSize)
{
var tmpImage = new GrayscaleFloatImage(image.Width, image.Height);
var kernel = new float[kernelSize * kernelSize];
for (var y = 0; y < image.Height; y++)
for (var x = 0; x < image.Width; x++)
{
for (var j = 0; j < kernelSize; j++)
for (var i = 0; i < kernelSize; i++)
{
var dx = x + i - kernelSize / 2;
var dy = y + j - kernelSize / 2;
if (dx < 0)
dx = 0;
if (dy < 0)
dy = 0;
if (dx >= image.Width)
dx = image.Width - 1;
if (dy >= image.Height)
dy = image.Height - 1;
kernel[i + j * kernelSize] = image[dx, dy];
}
kernel = kernel.OrderBy(e => e).ToArray();
tmpImage[x, y] = kernel[kernel.Length / 2 + 1];
}
return tmpImage;
}
static void Main(string[] args)
{
GrayscaleFloatImage input_image = ImageIO.FileToGrayscaleFloatImage(args[0]);
input_image = ExtendedRD(input_image, 4);
//input_image = temp_func(input_image, 2);
ImageIO.ImageToFile(input_image, args[2]);
}
public static void InversionProcess(GrayscaleFloatImage image)
{
for (var y = 0; y < image.Height; y++)
for (var x = 0; x < image.Width; x++)
{
image[x, y] = 255 - image[x, y];
}
}
public static GrayscaleFloatImage ClockWiseRotate(GrayscaleFloatImage image, int angle)
{
GrayscaleFloatImage resultImage;
switch (angle)
{
case 90:
resultImage = new GrayscaleFloatImage(image.Height, image.Width);
for (var y = 0; y < image.Height; y++)
for (var x = 0; x < image.Width; x++)
{
resultImage[image.Height - 1 - y, x] = image[x, y];
}
break;
case 180:
resultImage = new GrayscaleFloatImage(image.Width, image.Height);
for (var y = 0; y < image.Height; y++)
for (var x = 0; x < image.Width; x++)
{
resultImage[image.Width - 1 - x, image.Height - 1 - y] = image[x, y];
}
break;
case 270:
resultImage = new GrayscaleFloatImage(image.Height, image.Width);
for (var y = 0; y < image.Height; y++)
for (var x = 0; x < image.Width; x++)
{
resultImage[y, image.Width - 1 - x] = image[x, y];
}
break;
default:
var cos = Math.Cos(angle * 0.0174533);
var sin = Math.Sin(angle * 0.0174533);
var width = (int)Math.Floor(cos * image.Height + sin * image.Width);
var height = (int)Math.Floor(sin * image.Height + cos * image.Width);
resultImage = new GrayscaleFloatImage(width, height);
for (var y = 0; y < height; y++)
{
for (var x = 0; x < width; x++)
{
var b = sin * image.Height;
var hx = (x - b) * cos + y * sin;
var hy = -(x - b) * sin + y * cos;
float c = 0;
if (hx >= 1 && hy >= 1 && hx < image.Width - 1 && hy < image.Height - 1)
{
var x1 = (int)hx;
var y1 = (int)hy;
c = (float)((hy - y1) * ((x1 + 1 - hx) * image[x1, y1 + 1] + (hx - x1) * image[x1 + 1, y1 + 1]) +
(y1 + 1 - hy) * ((x1 + 1 - hx) * image[x1, y1] + (hx - x1) * image[x1 + 1, y1]));
}
resultImage[x, y] = c;
}
}
break;
}
return resultImage;
}
public static double Psnr(GrayscaleFloatImage image1, GrayscaleFloatImage image2)
{
var mse = Mse(image1, image2);
if (Math.Abs(mse) <= 0)
{
return(0);
}
return(10 * Math.Log10(255 * 255 / mse));
}
public static void InversionProcess(GrayscaleFloatImage image)
{
for (var y = 0; y < image.Height; y++)
{
for (var x = 0; x < image.Width; x++)
{
image[x, y] = 255 - image[x, y];
}
}
}
public static void FlipVertical(GrayscaleFloatImage image)
{
for (var y = 0; y < image.Height / 2; y++)
for (var x = 0; x < image.Width; x++)
{
var p = image[x, y];
image[x, y] = image[x, image.Height - 1 - y];
image[x, image.Height - 1 - y] = p;
}
}
public static void FlipHorizontal(GrayscaleFloatImage image)
{
for (var y = 0; y < image.Height; y++)
for (var x = 0; x < image.Width / 2; x++)
{
var p = image[x, y];
image[x, y] = image[image.Width - 1 - x, y];
image[image.Width - 1 - x, y] = p;
}
}
private static void NewGradient(GrayscaleFloatImage image, int r, float sig)
{
for (var y = 0; y < image.Height; y++)
{
for (var x = 0; x < image.Width; x++)
{
ImageX[x, y] = ImageY[x, y] = 0;
}
}
float s = 0, koef = 1 / (float)Math.Sqrt(2 * Math.PI * sig * sig);
for (var j = -r; j <= r; j++)
{
for (var i = -r; i <= r; i++)
{
s += Math.Abs((float)(koef * (-2) * i / (sig * sig) * Math.Exp(-((i * i + j * j) / (2 * sig * sig)))));
}
}
for (var y = 0; y < image.Height; y++)
{
for (var x = 0; x < image.Width; x++)
{
for (var j = -r; j <= r; j++)
{
for (var i = -r; i <= r; i++)
{
ImageX[x, y] += (float)(koef * (-2) * i / (sig * sig) * Math.Exp(-((i * i + j * j) / (2 * sig * sig)))) * image[x + i < 0 ? 0 : x + i >= image.Width ? image.Width - 1 : x + i, y + j < 0 ? 0 : y + j >= image.Height ? image.Height - 1 : y + j];
}
}
ImageX[x, y] = ImageX[x, y] / s;
}
}
for (var y = 0; y < image.Height; y++)
{
for (var x = 0; x < image.Width; x++)
{
for (var j = -r; j <= r; j++)
{
for (var i = -r; i <= r; i++)
{
ImageY[x, y] += (float)(koef * (-2) * j / (sig * sig) * Math.Exp(-((i * i + j * j) / (2 * sig * sig)))) * image[x + i < 0 ? 0 : x + i >= image.Width ? image.Width - 1 : x + i, y + j < 0 ? 0 : y + j >= image.Height ? image.Height - 1 : y + j];
}
}
ImageY[x, y] = ImageY[x, y] / s;
}
}
for (var x = 0; x < image.Width; x++)
{
for (var y = 0; y < image.Height; y++)
{
ImageGrad[x, y] = (float)Math.Sqrt(ImageY[x, y] * ImageY[x, y] + ImageX[x, y] * ImageX[x, y]);
}
}
}
public static GrayscaleFloatImage Bicubic(GrayscaleFloatImage image, double n)
{
int oldWidth = image.Width, oldHeight = image.Height;
var newWidth = (int)Math.Round(image.Width * n);
var newHeight = (int)Math.Round(image.Height * n);
var result = new GrayscaleFloatImage(newWidth, newHeight);
//
var arr = new float[4];
var temp = new float[4][];
for (var i = 0; i < 4; i++)
{
temp[i] = new float[4];
}
//
for (var y = 0; y < newHeight; y++)
{
for (var x = 0; x < newWidth; x++)
{
var x0 = (int)(x / n) - 1;
var y0 = (int)(y / n) - 1;
var x1 = (int)(x / n);
var y1 = (int)(y / n);
var x2 = (int)(x / n) + 1;
var y2 = (int)(y / n) + 1;
var x3 = (int)(x / n) + 2;
var y3 = (int)(y / n) + 2;
//
temp[0][0] = image[x0 < 0 ? 0 : x0 >= oldWidth ? oldWidth - 1 : x0, y0 < 0 ? 0 : y0 >= oldHeight ? oldHeight - 1 : y0];
temp[0][1] = image[x0 < 0 ? 0 : x0 >= oldWidth ? oldWidth - 1 : x0, y1 < 0 ? 0 : y1 >= oldHeight ? oldHeight - 1 : y1];
temp[0][2] = image[x0 < 0 ? 0 : x0 >= oldWidth ? oldWidth - 1 : x0, y2 < 0 ? 0 : y2 >= oldHeight ? oldHeight - 1 : y2];
temp[0][3] = image[x0 < 0 ? 0 : x0 >= oldWidth ? oldWidth - 1 : x0, y3 < 0 ? 0 : y3 >= oldHeight ? oldHeight - 1 : y3];
temp[1][0] = image[x1 < 0 ? 0 : x1 >= oldWidth ? oldWidth - 1 : x1, y0 < 0 ? 0 : y0 >= oldHeight ? oldHeight - 1 : y0];
temp[1][1] = image[x1 < 0 ? 0 : x1 >= oldWidth ? oldWidth - 1 : x1, y1 < 0 ? 0 : y1 >= oldHeight ? oldHeight - 1 : y1];
temp[1][2] = image[x1 < 0 ? 0 : x1 >= oldWidth ? oldWidth - 1 : x1, y2 < 0 ? 0 : y2 >= oldHeight ? oldHeight - 1 : y2];
temp[1][3] = image[x1 < 0 ? 0 : x1 >= oldWidth ? oldWidth - 1 : x1, y3 < 0 ? 0 : y3 >= oldHeight ? oldHeight - 1 : y3];
temp[2][0] = image[x2 < 0 ? 0 : x2 >= oldWidth ? oldWidth - 1 : x2, y0 < 0 ? 0 : y0 >= oldHeight ? oldHeight - 1 : y0];
temp[2][1] = image[x2 < 0 ? 0 : x2 >= oldWidth ? oldWidth - 1 : x2, y1 < 0 ? 0 : y1 >= oldHeight ? oldHeight - 1 : y1];
temp[2][2] = image[x2 < 0 ? 0 : x2 >= oldWidth ? oldWidth - 1 : x2, y2 < 0 ? 0 : y2 >= oldHeight ? oldHeight - 1 : y2];
temp[2][3] = image[x2 < 0 ? 0 : x2 >= oldWidth ? oldWidth - 1 : x2, y3 < 0 ? 0 : y3 >= oldHeight ? oldHeight - 1 : y3];
temp[3][0] = image[x3 < 0 ? 0 : x3 >= oldWidth ? oldWidth - 1 : x3, y0 < 0 ? 0 : y0 >= oldHeight ? oldHeight - 1 : y0];
temp[3][1] = image[x3 < 0 ? 0 : x3 >= oldWidth ? oldWidth - 1 : x3, y1 < 0 ? 0 : y1 >= oldHeight ? oldHeight - 1 : y1];
temp[3][2] = image[x3 < 0 ? 0 : x3 >= oldWidth ? oldWidth - 1 : x3, y2 < 0 ? 0 : y2 >= oldHeight ? oldHeight - 1 : y2];
temp[3][3] = image[x3 < 0 ? 0 : x3 >= oldWidth ? oldWidth - 1 : x3, y3 < 0 ? 0 : y3 >= oldHeight ? oldHeight - 1 : y3];
//
arr[0] = (float)(temp[0][1] + 0.5 * (float)(y / n - y1) * (temp[0][2] - temp[0][0] + (float)(y / n - y1) * (2.0 * temp[0][0] - 5.0 * temp[0][1] + 4.0 * temp[0][2] - temp[0][3] + (float)(y / n - y1) * (3.0 * (temp[0][1] - temp[0][2]) + temp[0][3] - temp[0][0]))));
arr[1] = (float)(temp[1][1] + 0.5 * (float)(y / n - y1) * (temp[1][2] - temp[1][0] + (float)(y / n - y1) * (2.0 * temp[1][0] - 5.0 * temp[1][1] + 4.0 * temp[1][2] - temp[1][3] + (float)(y / n - y1) * (3.0 * (temp[1][1] - temp[1][2]) + temp[1][3] - temp[1][0]))));
arr[2] = (float)(temp[2][1] + 0.5 * (float)(y / n - y1) * (temp[2][2] - temp[2][0] + (float)(y / n - y1) * (2.0 * temp[2][0] - 5.0 * temp[2][1] + 4.0 * temp[2][2] - temp[2][3] + (float)(y / n - y1) * (3.0 * (temp[2][1] - temp[2][2]) + temp[2][3] - temp[2][0]))));
arr[3] = (float)(temp[3][1] + 0.5 * (float)(y / n - y1) * (temp[3][2] - temp[3][0] + (float)(y / n - y1) * (2.0 * temp[3][0] - 5.0 * temp[3][1] + 4.0 * temp[3][2] - temp[3][3] + (float)(y / n - y1) * (3.0 * (temp[3][1] - temp[3][2]) + temp[3][3] - temp[3][0]))));
result[x, y] = (float)(arr[1] + 0.5 * (float)(x / n - x1) * (arr[2] - arr[0] + (float)(x / n - x1) * (2.0 * arr[0] - 5.0 * arr[1] + 4.0 * arr[2] - arr[3] + (float)(x / n - x1) * (3.0 * (arr[1] - arr[2]) + arr[3] - arr[0]))));
}
}
return(result);
}
public static void FlipHorizontal(GrayscaleFloatImage image)
{
for (var y = 0; y < image.Height; y++)
{
for (var x = 0; x < image.Width / 2; x++)
{
var p = image[x, y];
image[x, y] = image[image.Width - 1 - x, y];
image[image.Width - 1 - x, y] = p;
}
}
}
public static GrayscaleFloatImage Process(GrayscaleFloatImage image, double sigma)
{
var harris = new Harris(image, sigma);
BuildGradient(); //compute image grayscale gradient
BuildOrder2MomentMatrix(); //compute order 2 moment matrix;
BuildHarrisResponse(); //compute harris reponse for Corners
ApplyNonMaxSupression(); //apply non-maximum supression algorithm to eliminate the weak Corners
var result = WriteResultImage(image);
return(result);
}
public static double Mse(GrayscaleFloatImage image1, GrayscaleFloatImage image2)
{
double sum = 0;
var height = image1.Height;
var width = image1.Width;
for (var j = 0; j < height; j++)
for (var i = 0; i < width; i++)
{
sum += (image1.rawdata[i + j * width] - image2.rawdata[i + j * width]) * (image1.rawdata[i + j * width] - image2.rawdata[i + j * width]);
}
return sum / (height * width);
}
public static void FlipVertical(GrayscaleFloatImage image)
{
for (var y = 0; y < image.Height / 2; y++)
{
for (var x = 0; x < image.Width; x++)
{
var p = image[x, y];
image[x, y] = image[x, image.Height - 1 - y];
image[x, image.Height - 1 - y] = p;
}
}
}
public static GrayscaleFloatImage FileToGrayscaleFloatImage(string filename)
{
if (CheckPGM(filename))
{
return(ReadPGM(filename));
}
Bitmap B = new Bitmap(filename);
GrayscaleFloatImage res = BitmapToGrayscaleFloatImage(B);
B.Dispose();
return(res);
}
public static GrayscaleFloatImage Bicubic(GrayscaleFloatImage image, double n)
{
int oldWidth = image.Width, oldHeight = image.Height;
var newWidth = (int)Math.Round(image.Width * n);
var newHeight = (int)Math.Round(image.Height * n);
var result = new GrayscaleFloatImage(newWidth, newHeight);
//
var arr = new float[4];
var temp = new float[4][];
for (var i = 0; i < 4; i++)
temp[i] = new float[4];
//
for (var y = 0; y < newHeight; y++)
for (var x = 0; x < newWidth; x++)
{
var x0 = (int)(x / n) - 1;
var y0 = (int)(y / n) - 1;
var x1 = (int)(x / n);
var y1 = (int)(y / n);
var x2 = (int)(x / n) + 1;
var y2 = (int)(y / n) + 1;
var x3 = (int)(x / n) + 2;
var y3 = (int)(y / n) + 2;
//
temp[0][0] = image[x0 < 0 ? 0 : x0 >= oldWidth ? oldWidth - 1 : x0, y0 < 0 ? 0 : y0 >= oldHeight ? oldHeight - 1 : y0];
temp[0][1] = image[x0 < 0 ? 0 : x0 >= oldWidth ? oldWidth - 1 : x0, y1 < 0 ? 0 : y1 >= oldHeight ? oldHeight - 1 : y1];
temp[0][2] = image[x0 < 0 ? 0 : x0 >= oldWidth ? oldWidth - 1 : x0, y2 < 0 ? 0 : y2 >= oldHeight ? oldHeight - 1 : y2];
temp[0][3] = image[x0 < 0 ? 0 : x0 >= oldWidth ? oldWidth - 1 : x0, y3 < 0 ? 0 : y3 >= oldHeight ? oldHeight - 1 : y3];
temp[1][0] = image[x1 < 0 ? 0 : x1 >= oldWidth ? oldWidth - 1 : x1, y0 < 0 ? 0 : y0 >= oldHeight ? oldHeight - 1 : y0];
temp[1][1] = image[x1 < 0 ? 0 : x1 >= oldWidth ? oldWidth - 1 : x1, y1 < 0 ? 0 : y1 >= oldHeight ? oldHeight - 1 : y1];
temp[1][2] = image[x1 < 0 ? 0 : x1 >= oldWidth ? oldWidth - 1 : x1, y2 < 0 ? 0 : y2 >= oldHeight ? oldHeight - 1 : y2];
temp[1][3] = image[x1 < 0 ? 0 : x1 >= oldWidth ? oldWidth - 1 : x1, y3 < 0 ? 0 : y3 >= oldHeight ? oldHeight - 1 : y3];
temp[2][0] = image[x2 < 0 ? 0 : x2 >= oldWidth ? oldWidth - 1 : x2, y0 < 0 ? 0 : y0 >= oldHeight ? oldHeight - 1 : y0];
temp[2][1] = image[x2 < 0 ? 0 : x2 >= oldWidth ? oldWidth - 1 : x2, y1 < 0 ? 0 : y1 >= oldHeight ? oldHeight - 1 : y1];
temp[2][2] = image[x2 < 0 ? 0 : x2 >= oldWidth ? oldWidth - 1 : x2, y2 < 0 ? 0 : y2 >= oldHeight ? oldHeight - 1 : y2];
temp[2][3] = image[x2 < 0 ? 0 : x2 >= oldWidth ? oldWidth - 1 : x2, y3 < 0 ? 0 : y3 >= oldHeight ? oldHeight - 1 : y3];
temp[3][0] = image[x3 < 0 ? 0 : x3 >= oldWidth ? oldWidth - 1 : x3, y0 < 0 ? 0 : y0 >= oldHeight ? oldHeight - 1 : y0];
temp[3][1] = image[x3 < 0 ? 0 : x3 >= oldWidth ? oldWidth - 1 : x3, y1 < 0 ? 0 : y1 >= oldHeight ? oldHeight - 1 : y1];
temp[3][2] = image[x3 < 0 ? 0 : x3 >= oldWidth ? oldWidth - 1 : x3, y2 < 0 ? 0 : y2 >= oldHeight ? oldHeight - 1 : y2];
temp[3][3] = image[x3 < 0 ? 0 : x3 >= oldWidth ? oldWidth - 1 : x3, y3 < 0 ? 0 : y3 >= oldHeight ? oldHeight - 1 : y3];
//
arr[0] = (float)(temp[0][1] + 0.5 * (float)(y / n - y1) * (temp[0][2] - temp[0][0] + (float)(y / n - y1) * (2.0 * temp[0][0] - 5.0 * temp[0][1] + 4.0 * temp[0][2] - temp[0][3] + (float)(y / n - y1) * (3.0 * (temp[0][1] - temp[0][2]) + temp[0][3] - temp[0][0]))));
arr[1] = (float)(temp[1][1] + 0.5 * (float)(y / n - y1) * (temp[1][2] - temp[1][0] + (float)(y / n - y1) * (2.0 * temp[1][0] - 5.0 * temp[1][1] + 4.0 * temp[1][2] - temp[1][3] + (float)(y / n - y1) * (3.0 * (temp[1][1] - temp[1][2]) + temp[1][3] - temp[1][0]))));
arr[2] = (float)(temp[2][1] + 0.5 * (float)(y / n - y1) * (temp[2][2] - temp[2][0] + (float)(y / n - y1) * (2.0 * temp[2][0] - 5.0 * temp[2][1] + 4.0 * temp[2][2] - temp[2][3] + (float)(y / n - y1) * (3.0 * (temp[2][1] - temp[2][2]) + temp[2][3] - temp[2][0]))));
arr[3] = (float)(temp[3][1] + 0.5 * (float)(y / n - y1) * (temp[3][2] - temp[3][0] + (float)(y / n - y1) * (2.0 * temp[3][0] - 5.0 * temp[3][1] + 4.0 * temp[3][2] - temp[3][3] + (float)(y / n - y1) * (3.0 * (temp[3][1] - temp[3][2]) + temp[3][3] - temp[3][0]))));
result[x, y] = (float)(arr[1] + 0.5 * (float)(x / n - x1) * (arr[2] - arr[0] + (float)(x / n - x1) * (2.0 * arr[0] - 5.0 * arr[1] + 4.0 * arr[2] - arr[3] + (float)(x / n - x1) * (3.0 * (arr[1] - arr[2]) + arr[3] - arr[0]))));
}
return result;
}
public static GrayscaleFloatImage Gabor(GrayscaleFloatImage image, float[] kernel, int kernelWidth, int kernelHeight, int mode = 0)
{
var tmpImage = new GrayscaleFloatImage(image.Width, image.Height);
for (var y = 0; y < image.Height; y++)
{
for (var x = 0; x < image.Width; x++)
{
float sum = 0;
for (var j = 0; j < kernelHeight; j++)
{
for (var i = 0; i < kernelWidth; i++)
{
var dx = x + i - kernelWidth / 2;
var dy = y + j - kernelHeight / 2;
if (dx < 0)
{
dx = 0;
}
if (dy < 0)
{
dy = 0;
}
if (dx >= image.Width)
{
dx = image.Width - 1;
}
if (dy >= image.Height)
{
dy = image.Height - 1;
}
sum += image[dx, dy] * kernel[i + j * kernelWidth];
}
}
switch (mode)
{
case 1:
sum += 128;
break;
case 2:
sum = Math.Abs(sum);
break;
}
tmpImage[x, y] = sum;
}
}
return(tmpImage);
}
public static double Mse(GrayscaleFloatImage image1, GrayscaleFloatImage image2)
{
double sum = 0;
var height = image1.Height;
var width = image1.Width;
for (var j = 0; j < height; j++)
{
for (var i = 0; i < width; i++)
{
sum += (image1.rawdata[i + j * width] - image2.rawdata[i + j * width]) * (image1.rawdata[i + j * width] - image2.rawdata[i + j * width]);
}
}
return(sum / (height * width));
}
public Harris(GrayscaleFloatImage image, double sigma)
{
Width = image.Width;
Height = image.Height;
Corners = new int[Width * Height];
K = 0.05;
CornerTreshold = 9000000;
NmSupressWindowSize = 11;
Gray = new float[Width * Height];
Gray = image.rawdata;
GradX = new float[Width * Height];
GradY = new float[Width * Height];
Mx = new int[Width * Height];
My = new int[Width * Height];
Mxy = new int[Width * Height];
}
public static GrayscaleFloatImage WriteResultImage(GrayscaleFloatImage image)
{
for (var i = 2 * Width + 2; i < Width * Height - 2 * Width - 2; i++)
{
if ((byte)Corners[i] != 0)
{
for (var ii = -2; ii <= 2; ii++)
{
for (var jj = -2; jj <= 2; jj++)
{
image.rawdata[(i + ii * Width + jj)] = 1;
}
}
}
}
return(image);
}
public void InitializePath(string pathDir)
{
imgDir = Directory.GetFiles(pathDir).Where(a => a.Split("/").Last()[0] != '.').ToArray();
int count = imgDir.Count();
images = new List <float[]>();
for (int i = 0; i < count; i++)
{
Bitmap img = new Bitmap(imgDir[i]);
GrayscaleFloatImage a = ImageIO.BitmapToGrayscaleFloatImage(img);
images.Add(new float[a.rawdata.Length]);
a.rawdata.CopyTo(images[i], 0);
}
threads = new Thread[numProcs];
jobs = new ConcurrentQueue <float[]>(images);
}
public static GrayscaleFloatImage DownBilinear(GrayscaleFloatImage image, double n)
{
var width = (int)(image.Width / n);
var height = (int)(image.Height / n);
var result = new GrayscaleFloatImage(width, height);
//
var sigma = Math.Sqrt(n * n - 1);
var data = new double[image.rawdata.Length];
var template = new double[image.rawdata.Length];
for (var i = 0; i < image.rawdata.Length; i++)
{
data[i] = Convert.ToDouble(image.rawdata[i]);
}
//
ConvolutionGauss.GaussProcess(data, image.Width, image.Height, sigma: sigma, windowSize: (int)(sigma * 3), temp: template, dest: data);
//
for (var i = 0; i < image.rawdata.Length; i++)
{
image.rawdata[i] = Convert.ToSingle(data[i]);
}
for (var y = 0; y < height; y++)
{
var dy = y * n;
for (var x = 0; x < width; x++)
{
var dx = x * n;
if ((Math.Abs(dx % 1) <= 0) || (Math.Abs(dy % 1) <= 0))
{
result[x, y] = image[(int)dx, (int)dy];
}
else
{
var x1 = (int)dx;
var y1 = (int)dy;
result[x, y] = (float)((dy - y1) * ((x1 + 1 - dx) * image[x1, y1 + 1] + (dx - x1) * image[x1 + 1, y1 + 1]) +
(y1 + 1 - dy) * ((x1 + 1 - dx) * image[x1, y1] + (dx - x1) * image[x1 + 1, y1]));
}
}
}
return(result);
}
public static GrayscaleFloatImage MedianFilter(GrayscaleFloatImage image, int kernelSize)
{
var tmpImage = new GrayscaleFloatImage(image.Width, image.Height);
var kernel = new float[kernelSize * kernelSize];
for (var y = 0; y < image.Height; y++)
{
for (var x = 0; x < image.Width; x++)
{
for (var j = 0; j < kernelSize; j++)
{
for (var i = 0; i < kernelSize; i++)
{
var dx = x + i - kernelSize / 2;
var dy = y + j - kernelSize / 2;
if (dx < 0)
{
dx = 0;
}
if (dy < 0)
{
dy = 0;
}
if (dx >= image.Width)
{
dx = image.Width - 1;
}
if (dy >= image.Height)
{
dy = image.Height - 1;
}
kernel[i + j * kernelSize] = image[dx, dy];
}
}
kernel = kernel.OrderBy(e => e).ToArray();
tmpImage[x, y] = kernel[kernel.Length / 2 + 1];
}
}
return(tmpImage);
}
public static GrayscaleFloatImage Gabor(GrayscaleFloatImage image, float[] kernel, int kernelWidth, int kernelHeight, int mode = 0)
{
var tmpImage = new GrayscaleFloatImage(image.Width, image.Height);
for (var y = 0; y < image.Height; y++)
for (var x = 0; x < image.Width; x++)
{
float sum = 0;
for (var j = 0; j < kernelHeight; j++)
for (var i = 0; i < kernelWidth; i++)
{
var dx = x + i - kernelWidth / 2;
var dy = y + j - kernelHeight / 2;
if (dx < 0)
dx = 0;
if (dy < 0)
dy = 0;
if (dx >= image.Width)
dx = image.Width - 1;
if (dy >= image.Height)
dy = image.Height - 1;
sum += image[dx, dy] * kernel[i + j * kernelWidth];
}
switch (mode)
{
case 1:
sum += 128;
break;
case 2:
sum = Math.Abs(sum);
break;
}
tmpImage[x, y] = sum;
}
return tmpImage;
}
static GrayscaleFloatImage dir(ColorFloatImage image, float sigma)
{
string mode = "even";
int rad = (int)Math.Round(3 * sigma);
ColorFloatImage temp_img = img_expansion(image, mode, rad);
/*
* for (int y = 1; y < temp_image_x.Height + 1; y++)
* for (int x = 1; x < temp_image_x.Width + 1; x++)
* temp_image_x[x - 1, y - 1] = temp_image[x + 1, y] + (-1) * temp_image[x, y];
* for (int y = 1; y < temp_image_y.Height + 1; y++)
* for (int x = 1; x < temp_image_y.Width + 1; x++)
* temp_image_y[x - 1, y - 1] = temp_image[x, y + 1] + (-1) * temp_image[x, y];
*/
GrayscaleFloatImage temp_image = temp_img.ToGrayscaleFloatImage();
GrayscaleFloatImage out_img = new GrayscaleFloatImage(image.Width, image.Height);
float[,] Gx = g_kernel_deriv(sigma, "x");
float[,] Gy = g_kernel_deriv(sigma, "y");
for (int y = rad; y < image.Height + rad; y++)
{
for (int x = rad; x < image.Width + rad; x++)
{
float val_x = 0, val_y = 0;
int m = 0;
for (int j = y - rad; j < y + rad + 1; j++, m++)
{
int n = 0;
for (int k = x - rad; k < x + rad + 1; k++, n++)
{
val_x = val_x + Gx[n, m] * temp_image[k, j];
val_y = val_y + Gy[n, m] * temp_image[k, j];
}
}
if (val_x == 0 && val_y != 0)
{
out_img[x - rad, y - rad] = 64;
continue;
}
double theta = Math.Atan2(val_y - rad, val_x - rad) * (180 / Math.PI);
if (theta <= 22.5 && theta > -22.5 || theta <= -157.5 && theta > 157.5)
{
out_img[x - rad, y - rad] = 64; // ->
}
else if (theta <= 67.5 && theta > 22.5 || theta >= -157.5 && theta < -112.5)
{
out_img[x - rad, y - rad] = 192; // /
}
else if (theta > 67.5 && theta <= 112.5 || theta >= -112.5 && theta < -67.5)
{
out_img[x - rad, y - rad] = 128; // ^
}
else if (theta > 112.5 && theta <= 157.5 || theta >= -67.5 && theta < -22.5)
{
out_img[x - rad, y - rad] = 255; // \
}
}
}
return(out_img);
}
public static GrayscaleFloatImage DownBilinear(GrayscaleFloatImage image, double n)
{
var width = (int)(image.Width / n);
var height = (int)(image.Height / n);
var result = new GrayscaleFloatImage(width, height);
//
var sigma = Math.Sqrt(n * n - 1);
var data = new double[image.rawdata.Length];
var template = new double[image.rawdata.Length];
for (var i = 0; i < image.rawdata.Length; i++)
{
data[i] = Convert.ToDouble(image.rawdata[i]);
}
//
ConvolutionGauss.GaussProcess(data, image.Width, image.Height, sigma: sigma, windowSize: (int)(sigma * 3), temp: template, dest: data);
//
for (var i = 0; i < image.rawdata.Length; i++)
{
image.rawdata[i] = Convert.ToSingle(data[i]);
}
for (var y = 0; y < height; y++)
{
var dy = y * n;
for (var x = 0; x < width; x++)
{
var dx = x * n;
if ((Math.Abs(dx % 1) <= 0) || (Math.Abs(dy % 1) <= 0))
{
result[x, y] = image[(int)dx, (int)dy];
}
else
{
var x1 = (int)dx;
var y1 = (int)dy;
result[x, y] = (float)((dy - y1) * ((x1 + 1 - dx) * image[x1, y1 + 1] + (dx - x1) * image[x1 + 1, y1 + 1]) +
(y1 + 1 - dy) * ((x1 + 1 - dx) * image[x1, y1] + (dx - x1) * image[x1 + 1, y1]));
}
}
}
return result;
}
public static GrayscaleFloatImage Process(GrayscaleFloatImage image, float sigma, float th, float tl)
{
var canny = new Canny(image, sigma, th, tl);
var result = canny.Image;
return result;
}
public Canny(GrayscaleFloatImage image, float sigma, float th, float tl)
{
Image = image;
ImageX = new GrayscaleFloatImage(image.Width, image.Height);
ImageY = new GrayscaleFloatImage(image.Width, image.Height);
ImageGrad = new GrayscaleFloatImage(image.Width, image.Height);
MaxHysteresisThresh = th;
MinHysteresisThresh = tl;
Sigma = sigma;
NewGradient(Image, (int)(3 * Sigma), Sigma);
ImageGrad2 = new GrayscaleFloatImage(ImageGrad.Width, ImageGrad.Height);
for (var i = 1; i < Image.Width - 1; i++)
for (var j = 1; j < Image.Height - 1; j++)
{
var tang = Math.Round(Math.Atan2(ImageX[i, j], ImageY[i, j]) / (Math.PI / 4)) * (Math.PI / 4) - (Math.PI / 2);
var hi = Math.Sign(Math.Cos(tang));
var hj = -Math.Sign(Math.Sin(tang));
if (ImageGrad[i, j] < ImageGrad[i + hi, j + hj] || ImageGrad[i, j] < ImageGrad[i - hi, j - hj])
{
ImageGrad2[i, j] = 0;
}
else ImageGrad2[i, j] = ImageGrad[i, j];
}
ImageGrad = ImageGrad2;
var max = ImageGrad.rawdata.Max();
MinHysteresisThresh = max * MinHysteresisThresh;
MaxHysteresisThresh = max * MaxHysteresisThresh;
var stackX = new Stack<int>();
var stackY = new Stack<int>();
for (var i = 0; i < Image.Width; i++)
for (var j = 0; j < Image.Height; j++)
if (ImageGrad[i, j] > MaxHysteresisThresh)
{
ImageGrad[i, j] = 255;
stackX.Push(i);
stackY.Push(j);
}
else
if (ImageGrad[i, j] > MinHysteresisThresh) ImageGrad[i, j] = 128;
else ImageGrad[i, j] = 0;
while (stackX.Count != 0)
{
var x = stackX.Pop();
var y = stackY.Pop();
for (var i = 0; i < 8; i++)
{
var nx = x + Dx[i];
var ny = y + Dy[i];
if ((nx < 0) || (ny < 0) || (nx >= Image.Width) || (ny >= Image.Height)) continue;
if (ImageGrad[nx, ny] != 128) continue;
ImageGrad[nx, ny] = 255;
stackX.Push(nx);
stackY.Push(ny);
}
}
for (var i = 0; i < Image.Width; i++)
for (var j = 0; j < Image.Height; j++)
if (ImageGrad[i, j] == 255) Image[i, j] = 255;
else Image[i, j] = 0;
}
private static void NewGradient(GrayscaleFloatImage image, int r, float sig)
{
for (var y = 0; y < image.Height; y++)
for (var x = 0; x < image.Width; x++)
ImageX[x, y] = ImageY[x, y] = 0;
float s = 0, koef = 1 / (float)Math.Sqrt(2 * Math.PI * sig * sig);
for (var j = -r; j <= r; j++)
for (var i = -r; i <= r; i++)
s += Math.Abs((float)(koef * (-2) * i / (sig * sig) * Math.Exp(-((i * i + j * j) / (2*sig * sig)))));
for (var y = 0; y < image.Height; y++)
for (var x = 0; x < image.Width; x++)
{
for (var j = -r; j <= r; j++)
for (var i = -r; i <= r; i++)
{
ImageX[x, y] += (float)(koef * (-2) * i / (sig * sig) * Math.Exp(-((i * i + j * j) / (2*sig * sig)))) * image[x + i < 0 ? 0 : x + i >= image.Width ? image.Width - 1 : x + i, y + j < 0 ? 0 : y + j >= image.Height ? image.Height - 1 : y + j];
}
ImageX[x, y] = ImageX[x, y] / s;
}
for (var y = 0; y < image.Height; y++)
for (var x = 0; x < image.Width; x++)
{
for (var j = -r; j <= r; j++)
for (var i = -r; i <= r; i++)
{
ImageY[x, y] += (float)(koef * (-2) * j / (sig * sig) * Math.Exp(-((i * i + j * j) / (2*sig * sig)))) * image[x + i < 0 ? 0 : x + i >= image.Width ? image.Width - 1 : x + i, y + j < 0 ? 0 : y + j >= image.Height ? image.Height - 1 : y + j];
}
ImageY[x, y] = ImageY[x, y] / s;
}
for (var x = 0; x < image.Width; x++)
for (var y = 0; y < image.Height; y++)
ImageGrad[x, y] = (float)Math.Sqrt(ImageY[x, y] * ImageY[x, y] + ImageX[x, y] * ImageX[x, y]);
}
static GrayscaleFloatImage ExtendedRD(GrayscaleFloatImage img, int steps, int start = 1)
{
int[,] ridges_amount = new int[img.Width, img.Height];
double sigma = Math.Pow(Math.Sqrt(2), start - 1);
GrayscaleFloatImage[] image_array = new GrayscaleFloatImage[steps];
GrayscaleFloatImage[] new_image_array = new GrayscaleFloatImage[steps];
int rad = 0;
for (int i = 0; i < steps; ++i, sigma *= Math.Sqrt(2))
{
var t = matrix_der2(img, (float)sigma);
var matr = _solve_matr(t);
image_array[i] = RD(matr);
new_image_array[i] = nonmax(image_array[i].ToColorFloatImage(), (float)sigma);
ImageIO.ImageToFile(new_image_array[i], "a_" + i.ToString() + ".bmp");
new_image_array[i] = img_expansion(new_image_array[i].ToColorFloatImage(), "odd", rad).ToGrayscaleFloatImage();
}
int MAGIC_NUMBER = 3;
for (int i = 0; i < steps; ++i)
{
for (int y = 0; y < img.Height; ++y)
{
for (int x = 0; x < img.Width; ++x)
{
if (image_array[i][x, y] > 0)
{
ridges_amount[x, y]++;
}
}
}
}
GrayscaleFloatImage out_img = new GrayscaleFloatImage(img.Width, img.Height);
for (int y = 0; y < img.Height; ++y)
{
for (int x = 0; x < img.Width; ++x)
{
if (ridges_amount[x, y] >= MAGIC_NUMBER)
{
for (int i = steps - MAGIC_NUMBER - 1; i >= 0; --i)
{
bool f = true;
for (int j = 0; j < MAGIC_NUMBER; ++j)
{
bool an_f = false;
for (int a = -rad; a <= rad; ++a)
{
for (int b = -rad; b <= rad; ++b)
{
if (new_image_array[i][x + rad + a, y + rad + b] > 0 && !an_f)
{
if (out_img[x, y] == 0)
{
out_img[x, y] = new_image_array[i + j][x + rad + a, y + rad + b];
}
an_f = true;
}
}
}
if (!an_f)
{
f = false;
out_img[x, y] = 0;
}
}
if (f)
{
//out_img[x, y] /= MAGIC_NUMBER;
break;
}
}
}
}
}
return(out_img);
}
public static double Psnr(GrayscaleFloatImage image1, GrayscaleFloatImage image2)
{
var mse = Mse(image1, image2);
if (Math.Abs(mse) <= 0) return 0;
return 10 * Math.Log10(255 * 255 / mse);
}
public Canny(GrayscaleFloatImage image, float sigma, float th, float tl)
{
Image = image;
ImageX = new GrayscaleFloatImage(image.Width, image.Height);
ImageY = new GrayscaleFloatImage(image.Width, image.Height);
ImageGrad = new GrayscaleFloatImage(image.Width, image.Height);
MaxHysteresisThresh = th;
MinHysteresisThresh = tl;
Sigma = sigma;
NewGradient(Image, (int)(3 * Sigma), Sigma);
ImageGrad2 = new GrayscaleFloatImage(ImageGrad.Width, ImageGrad.Height);
for (var i = 1; i < Image.Width - 1; i++)
{
for (var j = 1; j < Image.Height - 1; j++)
{
var tang = Math.Round(Math.Atan2(ImageX[i, j], ImageY[i, j]) / (Math.PI / 4)) * (Math.PI / 4) - (Math.PI / 2);
var hi = Math.Sign(Math.Cos(tang));
var hj = -Math.Sign(Math.Sin(tang));
if (ImageGrad[i, j] < ImageGrad[i + hi, j + hj] || ImageGrad[i, j] < ImageGrad[i - hi, j - hj])
{
ImageGrad2[i, j] = 0;
}
else
{
ImageGrad2[i, j] = ImageGrad[i, j];
}
}
}
ImageGrad = ImageGrad2;
var max = ImageGrad.rawdata.Max();
MinHysteresisThresh = max * MinHysteresisThresh;
MaxHysteresisThresh = max * MaxHysteresisThresh;
var stackX = new Stack <int>();
var stackY = new Stack <int>();
for (var i = 0; i < Image.Width; i++)
{
for (var j = 0; j < Image.Height; j++)
{
if (ImageGrad[i, j] > MaxHysteresisThresh)
{
ImageGrad[i, j] = 255;
stackX.Push(i);
stackY.Push(j);
}
else
if (ImageGrad[i, j] > MinHysteresisThresh)
{
ImageGrad[i, j] = 128;
}
else
{
ImageGrad[i, j] = 0;
}
}
}
while (stackX.Count != 0)
{
var x = stackX.Pop();
var y = stackY.Pop();
for (var i = 0; i < 8; i++)
{
var nx = x + Dx[i];
var ny = y + Dy[i];
if ((nx < 0) || (ny < 0) || (nx >= Image.Width) || (ny >= Image.Height))
{
continue;
}
if (ImageGrad[nx, ny] != 128)
{
continue;
}
ImageGrad[nx, ny] = 255;
stackX.Push(nx);
stackY.Push(ny);
}
}
for (var i = 0; i < Image.Width; i++)
{
for (var j = 0; j < Image.Height; j++)
{
if (ImageGrad[i, j] == 255)
{
Image[i, j] = 255;
}
else
{
Image[i, j] = 0;
}
}
}
}
public static GrayscaleFloatImage Vessels(GrayscaleFloatImage image, int size, double sigma)
{
var angle = 15;
var images = new GrayscaleFloatImage[6];
for (var i = 0; i < 6; i++)
{
images[i] = Gabor(image, Filters.Gabor(6, 2, 3, angle, 1, 0), 6, 6);
angle += 30;
}
var result = new GrayscaleFloatImage(image.Width, image.Height);
for (var y = 0; y < image.Height; y++)
for (var x = 0; x < image.Width; x++)
{
result[x, y] = 0;
for (var i = 0; i < 6; i++)
{
if (images[i][x, y] <
result[x, y])
result[x, y] = images[i][x, y];
}
result[x, y] = Math.Abs(result[x, y]);
}
return result;
}
public static GrayscaleFloatImage CounterClockWiseRotate(GrayscaleFloatImage image, int angle)
{
GrayscaleFloatImage resultImage;
switch (angle)
{
case 90:
resultImage = new GrayscaleFloatImage(image.Height, image.Width);
for (var y = 0; y < image.Height; y++)
{
for (var x = 0; x < image.Width; x++)
{
resultImage[y, image.Width - 1 - x] = image[x, y];
}
}
break;
case 180:
resultImage = new GrayscaleFloatImage(image.Width, image.Height);
for (var y = 0; y < image.Height; y++)
{
for (var x = 0; x < image.Width; x++)
{
resultImage[image.Width - 1 - x, image.Height - 1 - y] = image[x, y];
}
}
break;
case 270:
resultImage = new GrayscaleFloatImage(image.Height, image.Width);
for (var y = 0; y < image.Height; y++)
{
for (var x = 0; x < image.Width; x++)
{
resultImage[image.Height - 1 - y, x] = image[x, y];
}
}
break;
default:
var cos = Math.Cos(angle * 0.0174533);
var sin = Math.Sin(angle * 0.0174533);
var width = (int)Math.Floor(cos * image.Width + sin * image.Height);
var height = (int)Math.Floor(sin * image.Width + cos * image.Height);
resultImage = new GrayscaleFloatImage(width, height);
for (var y = 0; y < height; y++)
{
for (var x = 0; x < width; x++)
{
var b = sin * image.Width;
var hx = (x) * cos - (y - b) * sin;
var hy = (x) * sin + (y - b) * cos;
float c = 0;
if (hx >= 1 && hy >= 1 && hx < image.Width - 1 && hy < image.Height - 1)
{
var x1 = (int)hx;
var y1 = (int)hy;
c = (float)((hy - y1) * ((x1 + 1 - hx) * image[x1, y1 + 1] + (hx - x1) * image[x1 + 1, y1 + 1]) +
(y1 + 1 - hy) * ((x1 + 1 - hx) * image[x1, y1] + (hx - x1) * image[x1 + 1, y1]));
}
resultImage[x, y] = c;
}
}
break;
}
return(resultImage);
}
static GrayscaleFloatImage temp_func(GrayscaleFloatImage image, float sigma)
{
GrayscaleFloatImage out_matr = new GrayscaleFloatImage(image.Width, image.Height);
float[,] Gxx = g_kernel(sigma, "yy");
//float[,] Gxy = g_kernel(sigma, "xy");
//float[,] Gyy = g_kernel(sigma, "yy");
int rad = (int)Math.Round(3 * sigma);
GrayscaleFloatImage temp_image = img_expansion(image.ToColorFloatImage(), "odd", rad).ToGrayscaleFloatImage();
float common_sum = 0;
for (int y = rad; y < image.Height + rad; ++y)
{
for (int x = rad; x < image.Width + rad; ++x)
{
float[,] q = new float[2, 2];
for (int m = -rad; m <= rad; ++m)
{
for (int n = -rad; n <= rad; ++n)
{
out_matr[x - rad, y - rad] += temp_image[x + n, y + m] * Gxx[rad + n, rad + m];
// q[0, 1] += temp_image[x + n, y + m] * Gxy[rad + n, rad + m];
// q[1, 1] += temp_image[x + n, y + m] * Gyy[rad + n, rad + m];
}
}
common_sum += out_matr[x - rad, y - rad];
}
}
Console.WriteLine(common_sum);
float max_one = 0;
float min_one = 0;
for (int y = 0; y < image.Height; ++y)
{
for (int x = 0; x < image.Width; ++x)
{
//out_matr[x, y] += 128;
if (out_matr[x, y] > max_one)
{
max_one = out_matr[x, y];
}
if (out_matr[x, y] < min_one)
{
min_one = out_matr[x, y];
}
}
}
min_one = -min_one;
//if (min_one > max_one)
// max_one = min_one;
for (int y = 0; y < image.Height; ++y)
{
for (int x = 0; x < image.Width; ++x)
{
out_matr[x, y] *= 255 / max_one / 2;
out_matr[x, y] += 128;
}
}
return(out_matr);
}
static GrayscaleFloatImage nonmax(ColorFloatImage image, float sigma)
{
int offset = 2;
string mode = "even";
ColorFloatImage temp_image = img_expansion(image, mode, offset);
temp_image = gradient(image, mode);
temp_image = img_expansion(temp_image, mode, offset);
GrayscaleFloatImage gray_grad = temp_image.ToGrayscaleFloatImage();
GrayscaleFloatImage dir_img = dir(image, sigma);
GrayscaleFloatImage out_img = new GrayscaleFloatImage(image.Width, image.Height);
float max_value = 0;
for (int y = 0; y < out_img.Height; y++)
{
for (int x = 0; x < out_img.Width; x++)
{
float M = gray_grad[x + offset, y + offset];
if (M > max_value)
{
max_value = M;
}
switch (dir_img[x, y])
{
case 0: // o
//break;
case 64: // ->
if (M < gray_grad[x + offset + 1, y + offset] ||
M < gray_grad[x + offset - 1, y + offset])
{
out_img[x, y] = 0;
}
else
{
out_img[x, y] = M;
}
break;
case 128: // ^
if (M < gray_grad[x + offset, y + offset + 1] ||
M < gray_grad[x + offset, y + offset - 1])
{
out_img[x, y] = 0;
}
else
{
out_img[x, y] = M;
}
break;
case 192: // /
if (M < gray_grad[x + offset + 1, y + offset + 1] ||
M < gray_grad[x + offset - 1, y + offset - 1])
{
out_img[x, y] = 0;
}
else
{
out_img[x, y] = M;
}
break;
case 255: // \
if (M < gray_grad[x + offset - 1, y + offset + 1] ||
M < gray_grad[x + offset + 1, y + offset - 1])
{
out_img[x, y] = 0;
}
else
{
out_img[x, y] = M;
}
break;
}
}
}
float mult = 255 / max_value;
for (int y = 0; y < out_img.Height; y++)
{
for (int x = 0; x < out_img.Width; x++)
{
out_img[x, y] *= mult;
}
}
return(out_img);
}
public float[] Load_Image(string path)
{
GrayscaleFloatImage image = ImageIO.FileToGrayscaleFloatImage(path);
return(image.rawdata);
}
