/// <summary>
/// foamliu, 2009/02/02, 彩色图片缩放.
/// </summary>
/// <param name="bmp"></param>
/// <param name="sr"></param>
/// <param name="sc"></param>
/// <returns></returns>
public static Bitmap Scale(Bitmap bmp, double sr, double sc)
{
int width, height;
int[][][] img, newImg;
Bitmap newBmp;
ImageConvert.Bitmap2MatColor(bmp, out img, out width, out height);
int newW = (int)(width * sc);
int newH = (int)(height * sr);
newImg = Util.BuildMatIntColor(newW, newH);
for (int y = 0; y < newH; y++)
{
for (int x = 0; x < newW; x++)
{
double[] input = new double[] { y, x, 1 };
double[] output = NcvMatrix.ScaleInvert(input, sr, sc);
int oldY = (int)Math.Round(output[0]);
int oldX = (int)Math.Round(output[1]);
if (Util.InRect(oldX, oldY, width, height))
{
// RGB
newImg[0][x][y] = img[0][oldX][oldY];
newImg[1][x][y] = img[1][oldX][oldY];
newImg[2][x][y] = img[2][oldX][oldY];
}
}
}
ImageConvert.Mat2BitmapColor(newImg, newW, newH, out newBmp);
return newBmp;
}
/// <summary>
/// foamliu, 2009/03/03, 边缘锐化.
/// 从原图像中减去拉普拉斯算子处理后的结果.
/// 我做的效果是图像锐化的同时产生了噪音. 与这个结果类似:
///
/// http://www.dfanning.com/ip_tips/sharpen.html
///
/// </summary>
/// <param name="bmp"></param>
/// <param name="type"></param>
/// <returns></returns>
public static Bitmap SharpenEdges(Bitmap bmp)
{
int width, height;
int[][][] mat, filtered = new int[3][][];
Bitmap newBmp;
ImageConvert.Bitmap2MatColor(bmp, out mat, out width, out height);
Convolution conv = new Convolution();
conv.Calculate(mat[0], ConvKernel.Laplacian_4, out filtered[0]);
conv.Calculate(mat[1], ConvKernel.Laplacian_4, out filtered[1]);
conv.Calculate(mat[2], ConvKernel.Laplacian_4, out filtered[2]);
NcvMatrix.MatSubtract(mat[0], filtered[0]);
NcvMatrix.MatSubtract(mat[1], filtered[1]);
NcvMatrix.MatSubtract(mat[2], filtered[2]);
GrayScaleImageLib.Normalize(mat[0]);
GrayScaleImageLib.Normalize(mat[1]);
GrayScaleImageLib.Normalize(mat[2]);
ImageConvert.Mat2BitmapColor(mat, width, height, out newBmp);
return(newBmp);
}
/// <summary>
/// foamliu, 2009/02/02, 彩色图片平移.
/// </summary>
/// <param name="bmp"></param>
/// <param name="tr"></param>
/// <param name="tc"></param>
/// <returns></returns>
public static Bitmap Translate(Bitmap bmp, double tr, double tc)
{
int width, height;
int[][][] img, newImg;
Bitmap newBmp;
ImageConvert.Bitmap2MatColor(bmp, out img, out width, out height);
newImg = Util.BuildMatIntColor(width, height);
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
double[] input = new double[] { y, x, 1 };
double[] output = NcvMatrix.TranslateInvert(input, tr, tc);
int oldY = (int)Math.Round(output[0]);
int oldX = (int)Math.Round(output[1]);
if (Util.InRect(oldX, oldY, width, height))
{
// RGB
newImg[0][x][y] = img[0][oldX][oldY];
newImg[1][x][y] = img[1][oldX][oldY];
newImg[2][x][y] = img[2][oldX][oldY];
}
}
}
ImageConvert.Mat2BitmapColor(newImg, width, height, out newBmp);
return newBmp;
}
public static Bitmap Gaussian(Bitmap bmp, double sigma)
{
int width, height;
int[][][] img, newImg;
Bitmap newBmp;
ImageConvert.Bitmap2MatColor(bmp, out img, out width, out height);
newImg = new int[3][][];
int n = 4;
ConvKernel kernel = Util.GetGaussianKernal(sigma, n);
Convolution conv = new Convolution();
// RGB
conv.Calculate(img[0], kernel, out newImg[0]);
conv.Calculate(img[1], kernel, out newImg[1]);
conv.Calculate(img[2], kernel, out newImg[2]);
ImageConvert.Mat2BitmapColor(newImg, width, height, out newBmp);
return(newBmp);
}
public static Bitmap Erosion(Bitmap bmp)
{
int width, height;
int[][][] mat, filtered = new int[3][][];
Bitmap newBmp;
ImageConvert.Bitmap2MatColor(bmp, out mat, out width, out height);
GrayScaleImageLib.Erosion(mat[0], StructuringElement.N4, out filtered[0]);
GrayScaleImageLib.Erosion(mat[1], StructuringElement.N4, out filtered[1]);
GrayScaleImageLib.Erosion(mat[2], StructuringElement.N4, out filtered[2]);
ImageConvert.Mat2BitmapColor(filtered, width, height, out newBmp);
return(newBmp);
}
public static Bitmap Median(Bitmap bmp, int k)
{
int width, height;
int[][][] mat, filtered = new int[3][][];
Bitmap newBmp;
ImageConvert.Bitmap2MatColor(bmp, out mat, out width, out height);
filtered[0] = Util.Median(mat[0], k);
filtered[1] = Util.Median(mat[1], k);
filtered[2] = Util.Median(mat[2], k);
//GrayValueImageLib.Normalize(filtered[0]);
//GrayValueImageLib.Normalize(filtered[1]);
//GrayValueImageLib.Normalize(filtered[2]);
ImageConvert.Mat2BitmapColor(filtered, width, height, out newBmp);
return(newBmp);
}
public static Bitmap Sobel(Bitmap bmp)
{
int width, height;
int[][][] img, newImg;
Bitmap newBmp;
ImageConvert.Bitmap2MatColor(bmp, out img, out width, out height);
newImg = new int[3][][];
Convolution conv = new Convolution();
// RGB
conv.CalculateEdge(img[0], ConvKernel.Sobel_Gx, ConvKernel.Sobel_Gy, out newImg[0], ConvNorm.Norm_1);
conv.CalculateEdge(img[1], ConvKernel.Sobel_Gx, ConvKernel.Sobel_Gy, out newImg[1], ConvNorm.Norm_1);
conv.CalculateEdge(img[2], ConvKernel.Sobel_Gx, ConvKernel.Sobel_Gy, out newImg[2], ConvNorm.Norm_1);
ImageConvert.Mat2BitmapColor(newImg, width, height, out newBmp);
return(newBmp);
}
public static Bitmap K_Mean(Bitmap bmp, int k)
{
int width, height;
int[][][] img, newImg;
Bitmap newBmp;
ImageConvert.Bitmap2MatColor(bmp, out img, out width, out height);
newImg = new int[3][][];
ConvKernel kernel = ConvKernel.GetKMeanKernal(k);
Convolution conv = new Convolution();
// RGB
conv.Calculate(img[0], kernel, out newImg[0]);
conv.Calculate(img[1], kernel, out newImg[1]);
conv.Calculate(img[2], kernel, out newImg[2]);
ImageConvert.Mat2BitmapColor(newImg, width, height, out newBmp);
return(newBmp);
}
/// <summary>
/// foamliu, 2009/02/02, 彩色图片旋转.
/// </summary>
/// <param name="bmp"></param>
/// <param name="alpha">旋转角度(弧度)</param>
/// <param name="bi">bilinear interpolation (双线性插值)</param>
/// <returns></returns>
public static Bitmap Rotate(Bitmap bmp, double alpha, bool bi)
{
int width, height;
int[][][] img, newImg;
Bitmap newBmp;
ImageConvert.Bitmap2MatColor(bmp, out img, out width, out height);
newImg = Util.BuildMatIntColor(width, height);
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
if (!bi)
{
double[] input = new double[] { y, x, 1 };
double[] output = NcvMatrix.RotateInvert(input, alpha);
int oldY = (int)Math.Round(output[0]);
int oldX = (int)Math.Round(output[1]);
if (Util.InRect(oldX, oldY, width, height))
{
// RGB
newImg[0][x][y] = img[0][oldX][oldY];
newImg[1][x][y] = img[1][oldX][oldY];
newImg[2][x][y] = img[2][oldX][oldY];
}
}
else
{
// p00 ------------- p01
// | |
// p10 ------------- p11
//
// 双线性插值需要更长的计算时间 (原来的5倍以上)
//
double[] input = new double[] { y, x, 1 };
double[] output = NcvMatrix.RotateInvert(input, alpha);
double newY = output[0];
double newX = output[1];
int p00Y = (int)Math.Floor(newY);
int p00X = (int)Math.Floor(newX);
int p01Y = (int)Math.Floor(newY);
int p01X = (int)Math.Ceiling(newX);
int p10Y = (int)Math.Ceiling(newY);
int p10X = (int)Math.Floor(newX);
int p11Y = (int)Math.Ceiling(newY);
int p11X = (int)Math.Ceiling(newX);
if (Util.InRect(p00X, p00Y, width, height)
&& Util.InRect(p01X, p01Y, width, height)
&& Util.InRect(p10X, p10Y, width, height)
&& Util.InRect(p11X, p11Y, width, height))
{
double a = newY - p00Y;
double b = newX - p00X;
for (int c = 0; c < 3; c++)
{
int g00 = img[c][p00X][p00Y];
int g01 = img[c][p01X][p01Y];
int g10 = img[c][p10X][p10Y];
int g11 = img[c][p11X][p11Y];
double g = b * (a * g11 + (1 - a) * g01) + (1 - b) * (a * g01 + (1 - a) * g00);
newImg[c][x][y] = (byte)Math.Round(g);
}
}
}
}
}
ImageConvert.Mat2BitmapColor(newImg, width, height, out newBmp);
return newBmp;
}