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isfilterseparable

Determine whether filter coefficients are separable

Description

isSeparable = isfilterseparable(H) returns logical 1 (true) when the filter kernel H is separable, and 0 (false) otherwise.

example

[isSeparable,hcol,hrow] = isfilterseparable(H) also returns the vertical coefficients hcol and horizontal coefficients hrow when the filter kernel, H, is separable. Otherwise, hcol and hrow are empty.

Examples

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Determine if the Gaussian filter created using the fspecial function is separable.

Create a Gaussian filter.

twoDimensionalFilter = fspecial('gauss');

Test the filter.

[isseparable,hcol,hrow] = isfilterseparable(twoDimensionalFilter)
isseparable = logical
   1

hcol = 3×1

   -0.1065
   -0.7870
   -0.1065

hrow = 1×3

   -0.1065   -0.7870   -0.1065

Input Arguments

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Filter kernel, specified as a non-sparse 2-D numeric or logical matrix.

Output Arguments

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Filter is separable, returned as logical 1 (true) when the filter is separable and 0 (false) when the filter is not separable.

Data Types: logical

Vertical coefficients when the filter kernel H is separable, returned as a numeric vector. When H is not separable, hcol is empty. If H is of data type single, then hcol is also of data type single. Otherwise, hcol is of data type double.

Horizontal coefficients when the filter kernel H is separable, returned as a numeric vector. When H is not separable, hrow is empty. If H is of data type single, then hrow is also of data type single. Otherwise, hrow is of data type double.

More About

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Separable two dimensional filters

Separable two-dimensional filters reflect the outer product of two vectors. Separable filters help reduce the number of calculations required.

A two-dimensional convolution calculation requires a number of multiplications equal to the width × height for each output pixel. The general case equation for a two-dimensional convolution is:

Y(m,n)=klH(k,l)U(mk,nl)

If the filter H is separable then,

H(k,l)=Hrow(k)Hcol(l)

Shifting the filter instead of the image, the two-dimensional equation becomes:

Y(m,n)=kHrow(k)lHcol(l)U(mk,nl)

This calculation requires only (width + height) number of multiplications for each pixel.

Algorithms

The isfilterseparable function uses the singular value decomposition svd function to determine the rank of the matrix.

Version History

Introduced in R2006a