Wolfram Language & System 11.0 (2016)|Legacy Documentation

This is documentation for an earlier version of the Wolfram Language.View current documentation (Version 11.2)

Structure Matrices & Convolution Kernels

The Wolfram Language provides built-in functions for generating standard structure matrices and convolution kernels in any number of dimensions, in a form that can be used directly in image processing, linear algebra, or other applications.


Shape Matrices

DiskMatrix BoxMatrix CrossMatrix DiamondMatrix

Convolution Kernels

GaussianMatrix Gaussian and Gaussian derivatives

ShenCastanMatrix exponential and exponential derivatives

SavitzkyGolayMatrix SavitzkyGolay smoothing and derivative kernel

GaborMatrix Gabor kernel

IdentityMatrix  ▪  DiagonalMatrix

ConstantArray constant array

CenterArray embed an array at the center of another array

SparseArray arbitrary sparse array

ArrayFlatten form a matrix from tiles

ArrayReshape reshape the array to new dimensions

ArrayPad add padding to an array

ArrayResample resample an array to new dimensions

ArrayFilter apply a function to array neighborhood blocks