ISIS Application Documentation
gauss | Standard View | TOC | Home |
Filter a cube through a kernel using Gaussian weight
Description
Categories
Groups
Examples
History
/ x^2+y^2 \ - | ----------- | G(x,y) = 1 \ 2(STDDEV)^2 / --------------- e^ 2(pi)(STDDEV)^2This formula creates a kernel that then runs through the image. The center of the kernel is at (0,0). This means that a 3x3 boxcar will be of the form
The kernel coordinates (-2,-2) (-1,-2) (0,-2) (1,-2) (2,-2) (-2,-1) (-1,-1) (0,-1) (1,-1) (2,-1) (-2, 0) (-1, 0) (0, 0) (1, 0) (2, 0) (-2, 1) (-1, 1) (0, 1) (1, 1) (2, 1) (-2, 2) (-1, 2) (0, 2) (1, 2) (2, 2) The kernel values (approx) 1 4 7 4 1 4 16 26 16 4 7 26 41 26 7 x 1/273 4 16 26 16 4 1 4 7 4 1
Name | Description |
---|---|
FROM | Input cube to be filtered |
TO | Output cube |
Name | Description |
---|---|
SIZE | Size of one side of the boxcar |
Name | Description |
---|---|
STDDEV | Standard Deviation |
Use this parameter to select the filename. All bands within the file will be filtered.
Type | cube |
---|---|
File Mode | input |
Filter | *.cub |
This file will contain the results of the filter, a blurred version of the input file.
Type | cube |
---|---|
File Mode | output |
This is the user specified size of the boxcar that will move through the image. The boxcar must be square, so the default value of 3 will result in a 3 x 3 boxcar. A value of five would result in a 5 x 5 boxcar moving through the image.
Type | integer |
---|---|
Default | 3 |
Odd | This value must be an odd number |
At the most basic level, standard deviation can be thought of in this context as the intensity of the blur being applied to the image. The higher this value, the more noise and detail will be removed. At a deeper level, standard deviation is described as the average distance from any single measurement of a set to the mean of that set.
Type | double |
---|---|
Default | 1.0 |
Minimum | 0 (exclusive) |
Using a 3 x 3 boxcar
gauss gui
|
Example GUI Screenshot of the GUI with parameters set to perform Gaussian smoothing with a 3 x 3 boxcar. |
The image before the filter
|
Input image before gauss.
Parameter Name:
FROM This is the image as it was taken originally. |
The image after the filter
|
Output image after gauss
Parameter Name:
TO This is the image after the gauss filter. Edges of the image are now much softer. Detail and noise has been removed. |
Using a 5 x 5 boxcar
gauss gui
|
Example GUI Screenshot of the GUI with parameters set to perform Gaussian smoothing with a 5 x 5 boxcar and 2.0 as the standard deviation. |
The image before the filter
|
Input image before gauss.
Parameter Name:
FROM This is the image as it was taken originally. |
The image after the filter
|
Output image after gauss
Parameter Name:
TO This is the image after the gauss filter. Edges of the image are now much softer. The blur is much more noticeable on account both of the larger boxcar and the larger standard deviation. |
Drew Davidson | 2004-08-05 | Original version |
Drew Davidson | 2004-08-06 | Added application test |
Drew Davidson | 2004-08-16 | Added examples |
Drew Davidson | 2005-06-27 | Fixed bug in boxcar size |
Brendan George | 2006-09-21 | Documentation fixes |
Kaitlyn Lee | 2018-02-15 | Removed the cout that was outputting e to the terminal. Fixes #5198. |