/// <summary>
/// 获得非极大值抑制后的图像
/// </summary>
/// <param name="Input"></param>
/// <param name="Edges"></param>
/// <param name="KernelSize"></param>
/// <param name="Sigma"></param>
public static void Suppression(Bitmap Input, out Bitmap Edges, int KernelSize, float Sigma)
{
ReadImage(Input);
GenerateGaussianKernel(KernelSize, Sigma, out float[,] GaussianKernel);
//高斯模糊处理
_grayImage = ConvolutionFilter2D(_grayImage, _width, _height, GaussianKernel, KernelSize);
//利用算子获得梯度与梯度方向数组
Soble(_grayImage, _width, _height, out _gradient, out _angle);
//非极大值抑制
Suppression(_image.Width, _height, _gradient, _angle);
Edges = new Bitmap(_width, _height);
LockBitmap lockBitmap = new LockBitmap(Edges);
lockBitmap.LockBits();
for (int i = 0; i < _width; i++)
{
for (int j = 0; j < _height; j++)
{
if (_gradient[i, j] > 255)
{
_gradient[i, j] = 255;
}
else if (_gradient[i, j] < 0)
{
_gradient[i, j] = 0;
}
lockBitmap.SetPixel(i, j, Color.FromArgb(_gradient[i, j], _gradient[i, j], _gradient[i, j]));
}
}
lockBitmap.UnlockBits();
}
/// <summary>
/// 将灰度化的图像储存于grayImage中
/// </summary>
static void ReadImage(Bitmap image)
{
_image = image;
_width = image.Width;
_height = image.Height;
_grayImage = new int[image.Width, image.Height];
LockBitmap lockBitmap = new LockBitmap(image);
lockBitmap.LockBits();
for (int i = 0; i < image.Width; i++)
{
for (int j = 0; j < image.Height; j++)
{
_grayImage[i, j] = (int)(0.3 * lockBitmap.GetPixel(i, j).R + 0.59 * lockBitmap.GetPixel(i, j).G + 0.11 * lockBitmap.GetPixel(i, j).B);
}
}
lockBitmap.UnlockBits();
}
/// <summary>
/// Canny检测
/// </summary>
/// <param name="Input"></param>
/// <param name="Edges"></param>
/// <param name="KernelSize"></param>
/// <param name="Sigma"></param>
/// <param name="ThrHigh"></param>
/// <param name="ThrLow"></param>
public static void DetectCannyEdges(Bitmap Input, out Bitmap Edges,
int KernelSize, float Sigma,
int ThrHigh, int ThrLow)
{
ReadImage(Input);
GenerateGaussianKernel(KernelSize, Sigma, out float[,] GaussianKernel);
//高斯模糊处理
_grayImage = ConvolutionFilter2D(_grayImage, _width, _height, GaussianKernel, KernelSize);
//利用算子获得梯度与梯度方向数组
Soble(_grayImage, _width, _height, out _gradient, out _angle);
//非极大值抑制
Suppression(_image.Width, _height, _gradient, _angle);
int[,] EdgesMap = new int[_width, _height];
//双阈值检测与滞后处理
HysterisisThresholding(_gradient, _width, _height, ThrHigh, ThrLow, ref EdgesMap);
//获得处理后的图像
Edges = new Bitmap(_width, _height);
LockBitmap lockBitmap = new LockBitmap(Edges);
lockBitmap.LockBits();
for (int i = 0; i < _width; i++)
{
for (int j = 0; j < _height; j++)
{
if (EdgesMap[i, j] == 1)
{
lockBitmap.SetPixel(i, j, System.Drawing.Color.White);
}
else
{
lockBitmap.SetPixel(i, j, System.Drawing.Color.Black);
}
}
}
lockBitmap.UnlockBits();
}
/// <summary>
/// 获得高斯过滤后的图像
/// </summary>
/// <param name="Input"></param>
/// <param name="Edges"></param>
/// <param name="KernelSize"></param>
/// <param name="Sigma"></param>
public static void GaussianFilter(Bitmap Input, out Bitmap Edges, int KernelSize, float Sigma)
{
ReadImage(Input);
GenerateGaussianKernel(KernelSize, Sigma, out float[,] GaussianKernel);
//高斯模糊处理
_grayImage = ConvolutionFilter2D(_grayImage, _width, _height, GaussianKernel, KernelSize);
Edges = new Bitmap(_width, _height);
LockBitmap lockBitmap = new LockBitmap(Edges);
lockBitmap.LockBits();
for (int i = 0; i < _width; i++)
{
for (int j = 0; j < _height; j++)
{
lockBitmap.SetPixel(i, j, Color.FromArgb(_grayImage[i, j], _grayImage[i, j], _grayImage[i, j]));
}
}
lockBitmap.UnlockBits();
}