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.

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

Related Guides

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• Data Transforms and Smoothing
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• Image Neighborhood Processing
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• Signal Processing
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• Feature Detection
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• Wavelet Analysis
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• Time Series Analysis