【发布时间】：2023-03-19 13:29:01
【问题描述】：
public partial class Form1 : Form
{
public Form1()
{
InitializeComponent();
Bitmap image = DataConverter2d.ReadGray(StandardImage.LenaGray);
Array2d<double> dImage = DataConverter2d.ToDouble(image);
int newWidth = Tools.ToNextPowerOfTwo(dImage.Width) * 2;
int newHeight = Tools.ToNextPowerOfTwo(dImage.Height) * 2;
double n = 6;
double f0 = 0.5;
double theta = 60;
double a = 0.4;
Array2d<Complex> kernel2d = CustomFft(newWidth, newHeight, n, f0, theta, a);
dImage.PadTo(newWidth, newHeight);
Array2d<Complex> cImage = DataConverter2d.ToComplex(dImage);
Array2d<Complex> fImage = FourierTransform.ForwardFft(cImage);
// FFT convolution .................................................
Array2d<Complex> fOutput = new Array2d<Complex>(newWidth, newHeight);
for (int x = 0; x < newWidth; x++)
{
for (int y = 0; y < newHeight; y++)
{
fOutput[x, y] = fImage[x, y] * kernel2d[x, y];
}
}
Array2d<Complex> cOutput = FourierTransform.InverseFft(fOutput);
Array2d<double> dOutput = Rescale2d.Rescale(DataConverter2d.ToDouble(cOutput));
dOutput.CropBy((newWidth - image.Width) / 2, (newHeight - image.Height) / 2);
Bitmap output = DataConverter2d.ToBitmap(dOutput, image.PixelFormat);
Array2d<Complex> cKernel = FourierTransform.InverseFft(kernel2d);
cKernel = FourierTransform.RemoveFFTShift(cKernel);
Array2d<double> dKernel = DataConverter2d.ToDouble(cKernel);
Array2d<double> dLimitedKernel = Rescale2d.Limit(dKernel);
Bitmap kernel = DataConverter2d.ToBitmap(dLimitedKernel, image.PixelFormat);
pictureBox1.Image = image;
pictureBox2.Image = kernel;
pictureBox3.Image = output;
}
private double Basic(double u, double v, double n, double f0, double rad, double a, double b)
{
double ua = u + f0 * Math.Cos(rad);
double va = v + f0 * Math.Sin(rad);
double ut = ua * Math.Cos(rad) + va * Math.Sin(rad);
double vt = (-1) * ua * Math.Sin(rad) + va * Math.Cos(rad);
double p = ut/a;
double q = vt/b;
double sqrt = Math.Sqrt(p*p + q*q);
return 1.0 / (1.0+ 0.414 * Math.Pow(sqrt, 2*n));
}
private double Custom(double u, double v, double n, double f0, double theta, double a)
{
double rad1 = (Math.PI / 180) * (90-theta);
double rad2 = rad1 + Math.PI;
double b = (a / 5.0) / (2*n);
double ka = Basic(u, v, n, f0, rad1, a, b);
double kb = Basic(u, v, n, f0, rad2, a, b);
return Math.Max(ka, kb);
}
private Array2d<Complex> CustomFft(double sizeX, double sizeY, double n, double f0, double theta, double a)
{
double halfX = sizeX / 2;
double halfY = sizeY / 2;
Array2d<Complex> kernel = new Array2d<Complex>((int)sizeX, (int)sizeY);
for (double y = 0; y < sizeY; y++)
{
double v = y / sizeY;
for (double x = 0; x < sizeX; x++)
{
double u = x / sizeX;
double kw = Custom(u, v, n, f0, theta, a);
kernel[(int)x, (int)y] = new Complex(kw, 0);
}
}
return kernel;
}
}
我创建了一个 40 内核 filter bank，其中每个内核的大小相同但参数不同。
这组过滤器大约需要 55000 毫秒 来生成内核。
我怎样才能减少这个时间？
注意：以下行花费的时间最多：
Array2d<Complex> kernel2d = CustomFft(newWidth, newHeight, n, f0, theta, a);
。
创建内核库的示例源代码：
public partial class Form1 : Form
{
public Form1()
{
InitializeComponent();
Stopwatch sw = new Stopwatch();
sw.Start();
Bitmap image = DataConverter2d.Read(StandardImage.Scratch1);
int newWidth = Tools.ToNextPowerOfTwo(image.Width);
int newHeight = Tools.ToNextPowerOfTwo(image.Height);
List<FrequencyDomainKernel> list = new List<FrequencyDomainKernel>();
for (int i = 0; i < 40; i++)
{
FrequencyDomainKernel k= new FrequencyDomainKernel();
k.Size = new System.Drawing.Size(newWidth, newHeight);
k.theta = i;
k.Compute();
list.Add(k);
}
sw.Stop();
MessageBox.Show(sw.ElapsedMilliseconds.ToString());
}
}
注意：这不是可执行代码。这段代码只是为了说明我生成内核的方法。
【问题讨论】：
-
什么电话占用了时间？
-
@LeonardoSeccia，嵌套的 for 循环。
-
究竟是哪一行？是
k.Compute()吗？如果是这样，最好的办法是减小图像的宽度和高度...如果将DataConverter2d.Read(StandardImage.Scratch1);替换为new Bitmap(64,64)，性能会提高吗？ -
@LeonardoSeccia,
If you replace DataConverter2d.Read(StandardImage.Scratch1); with new Bitmap(64,64) does the performance improve?--- 是的。严重。 -
另见
Parallel.For和Parallel.ForEach。也可以使用那些额外的核心。 docs.microsoft.com/en-us/dotnet/standard/parallel-programming/…
标签： c# image-processing filter-bank