ISIS Application Documentation
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Filter a cube through a kernel using Gaussian weight
| Overview | Parameters | Example 1 | Example 2 | 
Description
    This program calculates weight based on the bell-shaped Gaussian
    curve. The weight is then applied to an image kernel in such a way as to
    create a filter that will move a weighted average through the image. The
     end result is a blurred image with reduced detail and noise. The Gaussian
     function that determines the weight for all of the values in the kernel is
     as follows
   
                                                  /   x^2+y^2   \
                                               - |  -----------  |
                G(x,y) =           1              \ 2(STDDEV)^2 /
      			    --------------- e^
			    2(pi)(STDDEV)^2
  
  This 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
  
  CategoriesRelated Objects and DocumentsApplicationsHistory
  | 
Parameter GroupsFiles
 boxcar
 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) | 
Example 1Using a 3 x 3 boxcar Description
      This example shows the use of the default standard deviation (1.0) and the
      default boxcar size (3). Since the boxcar must be square in this program,
      this means that a 3 x 3 boxcar will be used.
         
Command Line
gauss 
	    from= peaks.cub
	    to=gauss3x3.cub
	    size=3
	    STDDEV= 1.0
	  
 
	This example uses all of the default values specified by the program
	 
GUI Screenshot
 Input Image
 Output Image
  | 
Example 2Using a 5 x 5 boxcar Description
      This example shows the use of a larger standard deviation (2.0) and the
      larger boxcar (5). As with the last example, the single value of 5 will
      be applied to both the line size and sample size of the boxcar.
         
Command Line
gauss 
	    from= peaks.cub
	    to=bigblur.cub
	    size=5
	    STDDEV= 2.0
	  
 
	This example will create a more dramatic blur, as everything is larger
	than in the first example
	 
GUI Screenshot
 Input Image
 Output Image
  |