我正在研究频域隐写术，我的任务是利用FFT在JPEG图片中隐藏文本信息。我用C#编写了一些代码，它拍摄一张图片，准备FFT算法并使用FFT计算其频域。输入图片为here，FFT算法的结果为here。然后此代码得到文本消息，从图片中获取复数值并更改此复数值的最低有效位（LSB）。在此之后，我们在this pucture中修改了频域，如您所见，有一条从中心到右侧加密的消息。但是当我尝试在修改后的图片中使用IFFT时，输出的结果是white picture。很明显我在改变频域的时候损坏了图片。这段代码有什么问题吗？
下面是详细注解的代码：

// Uploading image
        var image = AForge.Imaging.Image.FromFile("input.jpg");

        // Find the nearest power of 2 dimensions
        int width = (int)Math.Pow(2, Math.Ceiling(Math.Log(image.Width, 2)));
        int height = (int)Math.Pow(2, Math.Ceiling(Math.Log(image.Height, 2)));
        // Resize the image to the nearest power of 2 dimensions
        Bitmap resizedImage = new Bitmap(image, width, height);

        // Converting image to grayscale
        Grayscale filter = new Grayscale(0.2125, 0.7154, 0.0721);
        Bitmap grayImage = filter.Apply(resizedImage);

        // Converting image to the ComplexImage
        ComplexImage complexImage = ComplexImage.FromBitmap(grayImage);

        // Applying FFT
        complexImage.ForwardFourierTransform();

        // Saving result of FFT
        complexImage.ToBitmap().Save("fourier.jpg");

        // -------------------------------------------------------------------------

        // Converting text message to binary
        string textMessage = "Hello world";
        byte[] messageBytes = Encoding.Unicode.GetBytes(textMessage);
        BitArray messageBits = new BitArray(messageBytes);

        // Embedding text bits into the frequency domain
        int bitIndex = 0;
        for (int y = complexImage.Height / 2; y < complexImage.Height; y++)
        {
            for (int x = complexImage.Width / 2; x < complexImage.Width; x++)
            {
                if (bitIndex >= messageBits.Length)
                {
                    break;
                }

                // Getting complex value of frequency
                Complex complexValue = complexImage.Data[y, x];

                // Replacing the LSB of the real and imaginary parts with a bit from the message
                complexValue.Re = SetLeastSignificantBit(complexValue.Re, messageBits[bitIndex++]);
                complexValue.Im = SetLeastSignificantBit(complexValue.Im, messageBits[bitIndex++]);

                // Applying new value
                complexImage.Data[y, x] = complexValue;
            }
        }

        // Setting LSB
        static float SetLeastSignificantBit(double value, bool bit)
        {
            int intValue = BitConverter.ToInt32(BitConverter.GetBytes(value), 0);
            intValue = bit ? (intValue | 1) : (intValue & ~1);
            return BitConverter.ToSingle(BitConverter.GetBytes(intValue), 0);
        }

        // -------------------------------------------------------------------------

        complexImage.ToBitmap().Save("fourier222.jpg");

        // Applying IFFT
        complexImage.BackwardFourierTransform();

        complexImage.ToBitmap().Save("output.jpg");

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