WienerFilter
WienerFilter[data,r]
removes noise from data by applying a range-r Wiener filter.
WienerFilter[data,r,ns]
assumes an additive noise power value ns.
WienerFilter[data,{r1,r2,…},…]
uses radius ri at level i in data.
Details and Options
- The data can be any of the following:
-
list arbitrary-rank numerical array tseries temporal data such as TimeSeries, TemporalData, … image arbitrary Image or Image3D object audio an Audio or Sound object - For multichannel images and audio signals, WienerFilter operates separately on each channel.
- WienerFilter[data,{r1,r2,…},…] applies a Wiener filter using a convolution kernel.
- WienerFilter assumes the index coordinate system for lists and images.
- WienerFilter takes a Padding option. The default setting is Padding->"Fixed".
- With setting Padding->None, WienerFilter[data,…] normally returns a result smaller than data.
Examples
open allclose allBasic Examples (3)
Scope (9)
Data (4)
Wiener filtering of signal with additive noise:
Apply WienerFilter to a grayscale image:
Generalizations & Extensions (1)
WienerFilter works with numerical sparse arrays:
Options (3)
Padding (3)
Smoothing with WienerFilter using different padding methods:
Applications (4)
Denoise an ultrasound image using WienerFilter:
Text
Wolfram Research (2010), WienerFilter, Wolfram Language function, https://reference.wolfram.com/language/ref/WienerFilter.html (updated 2016).
CMS
Wolfram Language. 2010. "WienerFilter." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2016. https://reference.wolfram.com/language/ref/WienerFilter.html.
APA
Wolfram Language. (2010). WienerFilter. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/WienerFilter.html