FFT卷积后的复数据重标

我已经测试了两个重标度函数,将它们应用于FFT卷积输出。

第一个是从 this link .

    public static void RescaleComplex(Complex[,] convolve)
    {
        int imageWidth = convolve.GetLength(0);
        int imageHeight = convolve.GetLength(1);

        double maxAmp = 0.0;
        for (int i = 0; i < imageWidth; i++)
        {
            for (int j = 0; j < imageHeight; j++)
            {
                maxAmp = Math.Max(maxAmp, convolve[i, j].Magnitude);
            }
        }
        double scale = 1.0 / maxAmp;
        for (int i = 0; i < imageWidth; i++)
        {
            for (int j = 0; j < imageHeight; j++)
            {
                convolve[i, j] = new Complex(convolve[i, j].Real * scale,
                    convolve[i, j].Imaginary * scale);
            }
        }
    }

^{这里的问题是不正确的对比度。}

第二个是从 this link .

    public static void RescaleComplex(Complex[,] convolve)
    {            
        int imageWidth = convolve.GetLength(0);
        int imageHeight = convolve.GetLength(1);

        double scale = imageWidth * imageHeight;

        for (int j = 0; j < imageHeight; j++)
        {
            for (int i = 0; i < imageWidth; i++)
            {
                double re = Math.Max(0.0, Math.Min(convolve[i, j].Real * scale, 1.0));
                double im = Math.Max(0.0, Math.Min(convolve[i, j].Imaginary * scale, 1.0));
                convolve[i, j] = new Complex(re, im);
            }
        }
    }

^{这里的输出是完全白色的。}

所以,你可以看到两个版本给出了一个正确的和另一个错误的输出。

我怎样才能解决这个难题?

.

^{注意。 矩阵是以下核心:}

 0  -1   0 
-1   5  -1 
 0  -1   0

^{源代码。 这是我的FFT卷积函数。}

    private static Complex[,] ConvolutionFft(Complex[,] image, Complex[,] kernel)
    {
        Complex[,] imageCopy = (Complex[,])image.Clone();
        Complex[,] kernelCopy = (Complex[,])kernel.Clone();
        Complex[,] convolve = null;

        int imageWidth = imageCopy.GetLength(0);
        int imageHeight = imageCopy.GetLength(1);

        int kernelWidth = kernelCopy.GetLength(0);
        int kernelHeight = kernelCopy.GetLength(1);

        if (imageWidth == kernelWidth && imageHeight == kernelHeight)
        {
            Complex[,] fftConvolved = new Complex[imageWidth, imageHeight];

            Complex[,] fftImage = FourierTransform.ForwardFFT(imageCopy);
            Complex[,] fftKernel = FourierTransform.ForwardFFT(kernelCopy);                

            for (int j = 0; j < imageHeight; j++)
            {
                for (int i = 0; i < imageWidth; i++)
                {
                    fftConvolved[i, j] = fftImage[i, j] * fftKernel[i, j];
                }
            }

            convolve = FourierTransform.InverseFFT(fftConvolved);

            RescaleComplex(convolve);

            convolve = FourierShifter.ShiftFft(convolve);
        }
        else
        {
            throw new Exception("Padded image and kernel dimensions must be same.");
        }

        return convolve;
    }