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image-processing

Separable filters

taught

A 2D kernel that factors into two 1D kernels (row and column), letting a 2D convolution be computed as two cheaper 1D passes.

Taught in

Separable filters
Digital Image Processing

Requires

2d-discrete-convolution-and-correlation required

Required by

Classical kernels: identity, box, Gaussian required
Sobel and Prewitt operators required

Local knowledge map

Local knowledge map

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Solid arrows are required prerequisites; dashed are recommended or helpful. Lower rows are more foundational. Click any box to jump to that concept.