GaussianFilter

GaussianFilter[image, r]
filters image by convolving with a Gaussian kernel of pixel radius r.

GaussianFilter[image, r, {n1, n2}]
convolves image with a kernel formed from the ^(th) derivatives of the discrete Gaussian.

GaussianFilter[image, {r, }, ...]
uses a Gaussian kernel with radius r and standard deviation .

GaussianFilter[image, {{r1, r2}, ...}]
uses radii etc. in vertical and horizontal directions.

GaussianFilter[data, ...]
applies Gaussian filtering to an array of data.

Details and OptionsDetails and Options

  • GaussianFilter is a linear smoothing filter commonly used in image processing applications.
  • GaussianFilter works with arbitrary grayscale or multichannel images, operating separately on each channel.
  • GaussianFilter works with 3D as well as 2D images, and also with data arrays of any rank.
  • GaussianFilter[image, r] is equivalent to GaussianFilter[image, {r, r/2}].
  • GaussianFilter[image, ...] by default gives a real image of the same dimensions as image.
  • GaussianFilter[image, r, {n1, n2}] computes the ^(th) Gaussian derivative of the vertical dimension in an image pointing downward and the ^(th) horizontal derivative pointing toward the right.
  • GaussianFilter can take the following options:
  • Method"Bessel"how to determine elements of the Gaussian matrix
    Padding"Fixed"padding method
    WorkingPrecisionAutomaticthe precision to use
    "Standardization"Truewhether to rescale and shift the Gaussian matrix to account for truncation
  • Possible settings for the Method option are and .
  • With a setting Padding->None, GaussianFilter[image, ...] normally gives an image smaller than image.

ExamplesExamplesopen allclose all

Basic Examples (5)Basic Examples (5)

Gaussian filter of a three-channel image, using a four-pixel radius:

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Apply an elliptic Gaussian to blur more in the horizontal direction:

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Vertical Gaussian derivative:

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Horizontal Gaussian derivative:

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Horizontal and vertical derivatives combined:

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Apply a Gaussian filter to a list of values:

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New in 7 | Last modified in 9
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