Linear and Nonlinear Filters

The Wolfram Language's highly optimized filtering capabilities provide a wide range of linear and modern nonlinear local filters, as well as a variety of nonlocal filters, which can be applied to arbitrary arrays of data and images.

ReferenceReference

Linear Filters

GaussianFilter Gaussian and Gaussian derivatives filtering of images and arrays

DerivativeFilter general-order derivative filter

MeanFilter  ▪  GradientFilter  ▪  LaplacianFilter  ▪  WienerFilter  ▪  MovingAverage

LowpassFilter  ▪  HighpassFilter  ▪  BandpassFilter  ▪  BandstopFilter  ▪  HilbertFilter  ▪  DifferentiatorFilter

ListConvolve, ListCorrelate convolve, correlate with any kernel

Convolution Kernels »

DiskMatrix  ▪  BoxMatrix  ▪  DiamondMatrix  ▪  CrossMatrix

GaussianMatrix  ▪  IdentityMatrix  ▪  SparseArray

Nonlinear Filters

MedianFilter  ▪  MinFilter  ▪  MaxFilter  ▪  MeanShiftFilter  ▪  EntropyFilter  ▪  CornerFilter  ▪  RidgeFilter  ▪  KuwaharaFilter  ▪  BilateralFilter

CellularAutomaton general cellular automaton

Nonlocal Filters

TotalVariationFilter  ▪  ListDeconvolve