本文用的是emgucv4.1，对图像进行离散傅里叶变换，之后使用高斯滤波，再还原滤波后的图
1、对原图进行离散变换，之后显示频率
//============================1、将输入图像扩展到最佳的尺寸，边界用0补充int m = CvInvoke.GetOptimalDFTSize(glMain8UC1.Rows);int n = CvInvoke.GetOptimalDFTSize(glMain8UC1.Cols);Mat padded = new Mat();CvInvoke.CopyMakeBorder(glMain8UC1, padded, 0, m - glMain8UC1.Rows, 0, n - glMain8UC1.Cols, BorderType.Constant);padded.ConvertTo(padded, DepthType.Cv32F); //将padded转换为Cv32F类型，此为傅里叶变换的实部//============================2、创建傅里立叶的实部和虚部//创建元素值都为0的zeroMat，此为傅里叶变换的虚部Mat zeroMat = Mat.Zeros(padded.Rows, padded.Cols, DepthType.Cv32F, 1);VectorOfMat matVector = new VectorOfMat(); //创建mat型向量matVector.Push(padded); //将padded压入matVector中matVector.Push(zeroMat); //将zeroMat压入matVector中//创建channel数为2的mat，用于存储傅里叶变换的实部和虚部Mat complexI = new Mat(padded.Size, DepthType.Cv32F, 2);CvInvoke.Merge(matVector, complexI); //将matVector中存储的2个mat，merge到complexI中//=============================3、创建mat，用于保存傅里叶变换的结果Mat fourier = new Mat(complexI.Size, DepthType.Cv32F, 2);//调用傅里叶变换函数Dft，进行傅里叶变换CvInvoke.Dft(complexI, fourier, DxtType.Forward, complexI.Rows);Mat tempFourier = new Mat(complexI.Size, DepthType.Cv32F, 2);fourier.CopyTo(tempFourier);//=============================4、对结果进行变换显示//将复数转换为幅值，即=>log(1+sqrt(Re(DFT(I)^2+Im(DFT(I)^2))Mat magnitudeImage = Magnitude(fourier);CvInvoke.Log(magnitudeImage, magnitudeImage);//若有奇数行或奇数列，则进行频谱裁剪magnitudeImage = new Mat(magnitudeImage, new Rectangle(0, 0, magnitudeImage.Cols & -2, magnitudeImage.Rows & -2));//重新排列傅里叶图像中的象限，使得原点位于图像中心SwitchQuadrants(ref magnitudeImage);CvInvoke.Normalize(magnitudeImage, magnitudeImage, 0, 255, NormType.MinMax, DepthType.Cv8U);CvInvoke.Imshow("fourier forward", magnitudeImage);2、对原图进行离散变换后，使用高斯滤波，再还原图像
//============================1、将输入图像扩展到最佳的尺寸，边界用0补充int m = CvInvoke.GetOptimalDFTSize(glMain8UC1.Rows);int n = CvInvoke.GetOptimalDFTSize(glMain8UC1.Cols);Mat padded = new Mat();CvInvoke.CopyMakeBorder(glMain8UC1, padded, 0, m - glMain8UC1.Rows, 0, n - glMain8UC1.Cols, BorderType.Constant);padded.ConvertTo(padded, DepthType.Cv32F); //将padded转换为Cv32F类型，此为傅里叶变换的实部//============================2、创建傅里立叶的实部和虚部//创建元素值都为0的zeroMat，此为傅里叶变换的虚部Mat zeroMat = Mat.Zeros(padded.Rows, padded.Cols, DepthType.Cv32F, 1);VectorOfMat matVector = new VectorOfMat(); //创建mat型向量matVector.Push(padded); //将padded压入matVector中matVector.Push(zeroMat); //将zeroMat压入matVector中//创建channel数为2的mat，用于存储傅里叶变换的实部和虚部Mat complexI = new Mat(padded.Size, DepthType.Cv32F, 2);CvInvoke.Merge(matVector, complexI); //将matVector中存储的2个mat，merge到complexI中//=============================3、创建mat，用于保存傅里叶变换的结果Mat fourier = new Mat(complexI.Size, DepthType.Cv32F, 2);//调用傅里叶变换函数Dft，进行傅里叶变换CvInvoke.Dft(complexI, fourier, DxtType.Forward, complexI.Rows);Mat tempFourier = new Mat(complexI.Size, DepthType.Cv32F, 2);fourier.CopyTo(tempFourier);//==============================4、对应的滤波卷积处理this.SwitchQuadrants(ref tempFourier);Mat gaoshiKernel = GMLib.GasMat(tempFourier.Size, 55);CvInvoke.MulSpectrums(tempFourier, gaoshiKernel, tempFourier, MulSpectrumsType.Default);this.SwitchQuadrants(ref tempFourier);//==============================5、反傅立叶变换Mat fourierInv = new Mat(fourier.Size, DepthType.Cv32F, 2);//注意，反变换时，必须用这个参数 DxtType.InvScaleCvInvoke.Dft(tempFourier, fourierInv, DxtType.InvScale, tempFourier.Rows);Mat mainInv32FC1 = Magnitude(fourierInv);Mat mainInv8UC1 = new Mat(mainInv32FC1.Size, DepthType.Cv8U, 1);CvInvoke.ConvertScaleAbs(mainInv32FC1, mainInv8UC1, 1.0, 1.0);CvInvoke.Imshow("mainInv", mainInv8UC1);3、完整程序在链接中