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Structure Matrices & Convolution Kernels—Wolfram Language Documentation

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• Functions
  • ArrayFilter
  • ArrayFlatten
  • ArrayPad
  • ArrayResample
  • ArrayReshape
  • BoxMatrix
  • CenterArray
  • ConstantArray
  • CrossMatrix
  • DiagonalMatrix
  • DiamondMatrix
  • DiskMatrix
  • GaborMatrix
  • GaussianMatrix
  • IdentityMatrix
  • SavitzkyGolayMatrix
  • ShenCastanMatrix
  • SparseArray
• Related Guides
  • Constructing Matrices
  • Mathematical Morphology
  • Neighborhood Processing
• Tech Notes
  • Structure Matrices and Convolution Kernels
  • Constructing Matrices

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.

DiskMatrix — BoxMatrix — CrossMatrix — DiamondMatrix —

GaussianMatrix — Gaussian and Gaussian derivatives

ShenCastanMatrix — exponential and exponential derivatives

SavitzkyGolayMatrix — Savitzky–Golay 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

▪
• Structure Matrices and Convolution Kernels
▪
• Constructing Matrices

▪
• Constructing Matrices
▪
• Mathematical Morphology
▪
• Neighborhood Processing

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