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ISIS Documentation

lowpass

Apply lowpass or blurring filter to a cube

This program applies a lowpass or blurring filter to a cube. An NxM boxcar is moved through the cube and average of the boxcar at each position is computed. This average, which effectively blurs the data, is written to the output cube. The user has the ability to choose which input pixels are filtered including 1) all pixels, 2) pixels within a user specified range, 3) pixels outside a user specified range, and 4) special pixels. In general, the larger the boxcar the more the output cube is blurred. For example, a 101x101 boxcar will cause more blurring than a 3x3 boxcar.

Categories

Related Applications to Previous Versions of ISIS

This program replaces the following application existing in previous versions of ISIS:
  • boxfilter

Related Objects and Documents

Applications

History

Eric Eliason1988-05-20 Original version
Jeff Anderson2002-07-10 Ported to Isis 3.0
Kim Sides2003-05-13 Added application test
Stuart Sides2003-05-16 Modified schema location from astogeology... to isis.astrogeology..."
Stuart Sides2003-07-29 Modified filename parameters to be cube parameters where necessary
Drew Davidson2005-08-17 Added examples
Brendan George2005-11-21 Modified user interface
Elizabeth Miller2005-11-22 Fixed appTest parameters and documentation
Brendan George2006-05-31 Added Minopt parameter, modified user interface
Brendan George2006-06-19 Reorganized user interface

Parameters

Files

Input cube to filter
Type cube
File Mode input
Filter *.cub

The resultant filtered cube
Type cube
File Mode output

Boxcar Size

This is the total number of samples in the boxcar. It must be odd and can not exceed twice the number of samples in the cube. In general, the size of the boxcar does not cause the program to operate significantly slower.
Type integer
Minimum 1 (inclusive)
Odd This value must be an odd number

This is the total number of lines in the boxcar. It must be odd and can not exceed twice the number of lines in the cube. In general, the size of the boxcar does not cause the program to operate significantly slower.
Type integer
Minimum 1 (inclusive)
Odd This value must be an odd number

Boxcar Settings

Valid minimum pixel value that will be used in boxcar computation. If a pixel value is less than LOW then it will not be used when computing the average.
Type double
Internal Default Use all pixels
Less Than HIGH

Valid maximum pixel value that will be used in boxcar computation. If a pixel value is greater than HIGH then it will not be used when computing the average.
Type double
Internal Default Use all pixels
Greater Than LOW

This parameter determines whether the minimum parameter is to be interpreted as a count of pixels, or a percentage of all pixels in the boxcar.
Type string
Default COUNT
Option List:
Option Brief Description
COUNT Minimum valid pixel count This option indicates that the minimum is a minimum count of pixels required for filtering.
PERCENTAGE Minimum valid pixel percentage This option indicates the the minimum parameter is to be interpreted as a percentage of the total pixels in the boxcar.

This option is the minimum number of valid pixels required in a boxcar for filtering to begin.
Type double
Default 1

This determines what to put in the center pixel, in the event that there aren't enough valid, non-special pixels in the boxcar to meet the minimum. The default is to replace it with the current value, and the other option is to replace it with NULL.
Type string
Default CENTER
Option List:
Option Brief Description
CENTER Center pixel value This sets the center pixel of the boxcar to whatever was already there, in the event that there are not enough valid, non-Special pixels to meet minimum requirements.
NULL Pixel value Null This sets the center pixel of the boxcar to the special pixel value fo "Null", if there are not enough valid, non-Special pixels to meet minimum requirements.

Non-Special Pixel Filtering

These options choose which pixels to filter. The options are ALL, VALID and INVALID. If the first is chosen, the filter will be run on all pixels inside the LOW-HIGH range, and all Specials declared valid. If the second option is chosen, the filter is only run when the center pixel is valid, and the third option only runs the filter when the center is invalid. Regardless of which option is chosen, the average is only calculated from values between LOW and HIGH.
Type string
Default ALL
Option List:
Option Brief Description
ALL Filter All Pixels This is the option if you wish to filter all pixels, regardless of validitity. It will only filter those Special Pixels indicated by the user to be filtered. Also, the average will only be calculated from the pixels with values between LOW and HIGH.
INSIDE Filter Pixels Between Low and High This is the option if you only wish to run the filter when the center pixel is valid. The filter will only run if there are enough valid pixels to meet the requirements set by LOW, HIGH, and MINIMUM
OUTSIDE Filter Pixels Outside Low and High This is the option if you only wish to run the filter when the center pixel is invalid. The filter will only run if there are enough valid pixels to meet the requirements set by LOW, HIGH, and MINIMUM

Special Pixel Filtering

If the center pixel of a boxcar is NULL, and this box is checked, the pixel will be overwritten with the average value of the boxcar as a whole. If this box is not checked, the pixel will be left alone.
Type boolean
Default TRUE

If the center pixel of a boxcar is HRS, and this box is checked, the pixel will be overwritten with the average value of the boxcar as a whole. If this box is not checked, the pixel will be treated according to the REPLACEMENT parameter.
Type boolean
Default TRUE

If the center pixel of a boxcar is HIS, and this box is checked, the pixel will be overwritten with the average value of the boxcar as a whole. If this box is not checked, the pixel will be treated according to the REPLACEMENT parameter.
Type boolean
Default TRUE

If the center pixel of a boxcar is LRS, and this box is checked, the pixel will be overwritten with the average value of the boxcar as a whole. If this box is not checked, the pixel will be treated according to the REPLACEMENT parameter.
Type boolean
Default TRUE

If the center pixel of a boxcar is LIS, and this box is checked, the pixel will be overwritten with the average value of the boxcar as a whole. If this box is not checked, the pixel will treated according to the REPLACEMENT parameter.
Type boolean
Default TRUE

Example 1

Running a 3x3 boxcar on all pixels

The lowpass filter

Command Line

This configuration creates a relatively small filter, resulting in a slight amount of blurring.
lowpass from= peaks.cub to=3x3lowpass.cub samples=3 lines=3

GUI Screenshot

lowpass gui

Example GUI

lowpass gui

Screenshot of the GUI set to filter all pixels for the image using a three by three boxcar. Note that as many of the default parameters as are allowed are being used.

Input Image

The image before the filter

Input image before the lowpass filter.

The image before the filter

Parameter Name: FROM

Here we see the original cube. The areas of greatest interest are those with a great deal of contrast such as edges.

Output Image

The image after the filter

Output image after lowpass

The image after the filter

Parameter Name: TO

After the filter, the entire image is somewhat softer. The difference may be hard to detect on uniform areas, but the sections of the image that previously were sharply contrasted are now blurred. As this particular configuration has been set for a small filter, the results are obtained quickly and are more subtle than a large filter.

Example 2

Running a 21x21 boxcar on all pixels

The lowpass filter is used again here, but at a much more intense level

Command Line

This configuration creates a relatively large filter, resulting in a great amount of blurring.
lowpass from= peaks.cub to=bigLowpass.cub samples=21 lines=21

GUI Screenshot

lowpass gui

Example GUI

lowpass gui

Screenshot of the GUI set to filter all pixels for the image using a 21 by 21 boxcar. This configuration will be slightly slower than in the previous example, due to the increased boxcar size.

Input Image

The image before the filter

Input image before the lowpass filter.

The image before the filter

Parameter Name: FROM

Here we see the original cube. The areas of greatest interest are those with a great deal of contrast such as edges.

Output Image

The image after the filter

Output image after lowpass

The image after the filter

Parameter Name: TO

As seen here, the 21 by 21 boxcar blurs the image to a great extent. In fact, there seems to be little purpose for ever using a square boxcar this large, except for the purpose of illustrating the effect of the lowpass.