Gaussian filter
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<math>G_{2D}(x,y,\sigma)=\frac{1}{\sqrt{2 \pi \sigma^2}}e^{-\frac{x^2+y^2}{2\sigma^2}}</math> where <math>\sigma</math> determines the ''width'' of the kernel. | <math>G_{2D}(x,y,\sigma)=\frac{1}{\sqrt{2 \pi \sigma^2}}e^{-\frac{x^2+y^2}{2\sigma^2}}</math> where <math>\sigma</math> determines the ''width'' of the kernel. | ||
== Gaussian filter using OTB == | == Gaussian filter using OTB == | ||
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* In the search engine of the Processing Toolbox, type '''Smoothing''' and select '''Smoothing (gaussian)''' under Image Filtering of the Orfeo Toolbox. | * In the search engine of the Processing Toolbox, type '''Smoothing''' and select '''Smoothing (gaussian)''' under Image Filtering of the Orfeo Toolbox. | ||
* Under the Parameters tab, select a '''single band or a multiband file''' as input layer. | * Under the Parameters tab, select a '''single band or a multiband file''' as input layer. |
Revision as of 10:03, 21 June 2019
The Gaussian smoothing filter is used for noise reduction and removing details. The filter is similar to the arithmetic mean filter but it uses a different kernel that represents the shape of a 2 dimensional Gaussian distribution which is defined as \(G_{2D}(x,y,\sigma)=\frac{1}{\sqrt{2 \pi \sigma^2}}e^{-\frac{x^2+y^2}{2\sigma^2}}\) where \(\sigma\) determines the width of the kernel.
Gaussian filter using OTB
- In the search engine of the Processing Toolbox, type Smoothing and select Smoothing (gaussian) under Image Filtering of the Orfeo Toolbox.
- Under the Parameters tab, select a single band or a multiband file as input layer.
- Select gaussian from the drop-down list as Smoothing Type.
- Adjust the Radius of a circular element in pixel size.
Gaussian filter using SAGA
- In the search engine of the Processing Toolbox, type Gaussian and select Gaussian filter under Raster Filter of SAGA.
- Under the Parameters tab, select a single band file as Grid.
- Select Circle from the drop-down list as Search Mode.
- Choose 1 as Standard deviation
- Use the 3 pixels as Radius.