filters data by replacing every value by the minimum value in its range-r neighborhood.


uses ri for filtering the ^(th)dimension in data.


  • MinFilter is a nonlinear filter commonly used to locally smooth data and diminish salt-like noise, where the amount of smoothing is dependent on the value of r.
  • The function applied to each range-r neighborhood is Min.
  • The data can be any of the following:
  • listarbitrary-rank numerical array
    tseriestemporal data such as TimeSeries, TemporalData,
    imagearbitrary Image or Image3D object
    audioan Audio object
  • For multichannel images, MinFilter replaces each pixel by a pixel in its neighborhood that has the minimum total intensity, averaged over all channels.
  • MinFilter[data,{r1,r2,}] computes the minimum value in blocks centered on each sample.
  • MinFilter assumes the index coordinate system for lists and images.
  • At the data boundaries, MinFilter uses smaller neighborhoods.


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Basic Examples  (3)

Minimum filter of a list:

Filter a TimeSeries:

Minimum filtering of a color image:

Scope  (12)

Data  (7)

Minimum filtering of a numeric vector:

Filtering a symbolic array:

Minimum filtering of a 2D array:

Minimum filtering of a list of Quantity objects:

Filter an Audio signal:

Filtering a 2D grayscale image:

Minimum filter of a 3D image:

Parameters  (5)

Specify one radius to be used in all directions:

Increasing the radius will result in darker images:

Minimum filtering just in the first direction:

Filtering just in the second direction:

Minimum filtering of a 3D image in the vertical direction only:

Filtering of a 3D image in the horizontal planes only:

Applications  (3)

Use minimum filtering to remove thin, bright objects:

Remove salt noise from an image:

Use minimum filtering to locate borders in an image:

Properties & Relations  (2)

For single-channel images, MinFilter is the same as ImageFilter with function Min:

For single-channel images, MinFilter is the same as Erosion with a box structuring element:

Introduced in 2008
Updated in 2015