removes noise from data by applying a range-r Wiener filter.


assumes an additive noise power value ns.


uses radius ri at level i in data.

Details and Options


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Basic Examples  (3)

Wiener filtering of a list:

Filter a TimeSeries:

Filter an image:

Scope  (9)

Data  (4)

Wiener filtering of signal with additive noise:

Filter an audio signal:

Apply WienerFilter to a grayscale image:

Wiener filtering of a 3D image:

Parameters  (5)

Specify one radius to be used in all directions:

Increasing the radius will result in smoother results:

Wiener filtering just in the first direction:

Second direction:

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

Filtering of the horizontal planes only:

Use different estimates of noise power:

Generalizations & Extensions  (1)

WienerFilter works with numerical sparse arrays:

Options  (3)

Padding  (3)

Smoothing with WienerFilter using different padding methods:

By default, a "Fixed" padding is used:

Specify a custom padding:

Applications  (4)

Denoise a grayscale image:

Denoise an ultrasound image using WienerFilter:

Remove Gaussian color noise from an image:

Unsharp masking using Wiener filtering:

Wolfram Research (2010), WienerFilter, Wolfram Language function, (updated 2016).


Wolfram Research (2010), WienerFilter, Wolfram Language function, (updated 2016).


Wolfram Language. 2010. "WienerFilter." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2016.


Wolfram Language. (2010). WienerFilter. Wolfram Language & System Documentation Center. Retrieved from


@misc{reference.wolfram_2024_wienerfilter, author="Wolfram Research", title="{WienerFilter}", year="2016", howpublished="\url{}", note=[Accessed: 30-May-2024 ]}


@online{reference.wolfram_2024_wienerfilter, organization={Wolfram Research}, title={WienerFilter}, year={2016}, url={}, note=[Accessed: 30-May-2024 ]}