Gaussian filter
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| − | 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 | + | 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 <math>G_{2D}(x,y,\sigma)=\frac{1}{\sqrt{2 \pi \sigma^2}}e^{-\frac{x^2+y^2}{2\sigma^2}}</math> |
<math>G_{2D}(x,y,\sigma)=\frac{1}{\sqrt{2 \pi \sigma^2}}e^{-\frac{x^2+y^2}{2\sigma^2}</math> | <math>G_{2D}(x,y,\sigma)=\frac{1}{\sqrt{2 \pi \sigma^2}}e^{-\frac{x^2+y^2}{2\sigma^2}</math> | ||
* 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. | ||
Revision as of 15:55, 20 November 2017
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 \(G_{2D}(x,y,\sigma)=\frac{1}{\sqrt{2 \pi \sigma^2}}e^{-\frac{x^2+y^2}{2\sigma^2}}\) \(G_{2D}(x,y,\sigma)=\frac{1}{\sqrt{2 \pi \sigma^2}}e^{-\frac{x^2+y^2}{2\sigma^2}\)
- 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.
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