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ISIS 3 Application Documentation

speclowpass

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Apply spectral low pass filter to a cube

Description
Categories
Groups
Examples
History

Description

This program applies a spectral low pass filter to a cube. A spectral filter works between bands as opposed to a spacial operation on a single band. Lowpass filter means it will be subtracting the average from the original pixel.

Categories

Related Applications to Previous Versions of ISIS

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

Related Objects and Documents

Applications

Parameter Groups

Files

Name Description
FROM Input file
TO Filtered output cube

Boxcar Size

Name Description
BANDS Number of bands in boxcar

Boxcar Settings

Name Description
LOW Minimum valid DN
HIGH Maximum valid DN

Files: FROM

Description

Input cube to filter

Type cube
File Mode input
Filter *.cub

Files: TO

Description

The resultant filtered cube

Type cube
File Mode output
Filter *.cub

Boxcar Size: BANDS

Description

This is the total number of bands in the boxcar. It must be odd and can not exceed twice the number of bands 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: LOW

Description

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

Boxcar Settings: HIGH

Description

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

Examples

Example 1

Example of usage of the spectral lowpass filter.

Description

This example shows a spectral lowpass filter being applied to the image with a 5 depth boxcar. This cube has 256 bands so 5 is relatively small. Although no averaging is done within a single band, the averaging of the pixels of many bands will cause some averaging and smoothing of the image if there is much difference between bands. Here is an image which highlights which pixels a single pass would average. The image shows a 9x9 dot instead of a single pixel highlighted to make it more visible. In this picture the boxcar would be seven or more bands, with the output pixel being one of the visible pixels. Depending on how large the boxcar was many of the values taken in could not be original, at a minimum, one value will be mirrored since there are only six available bands.

Command Line

speclowpass from=/work1/mboyd/CM_1514302573_1.cub to=/work1/mboyd/postlow.cub bands=5
This example will filter the image using 5 bands and no limits on high or low.

GUI Screenshot

This program's GUI

Example GUI

Screenshot of the GUI wit h parameters set to perform the spechighpass filter with a 5 band boxcar on the image CM_1514302573_1.ir.cub.

Input Image

The image graph before the filter

Input image spectral graph before speclowpass filter

Parameter Name: FROM

This is the spectral plot of the center point of the image, (32, 32), and shows all bands, 1- 256. No averaging has been applied, this is clear partialy because of th extreme peaks visible in the first half. The peaks are related to values which differ significantly from the bands around them.

Output Image

The image graph after the filter

Output image spectral graph after being filtered

Parameter Name: TO

This is the image after the filter. Although there are still peaks, everything has been smoothed. In the before image the peaks were sharp where as now they are more curved. Differences have been leveled out to some extent.

Example 2

Example of usage of the spectral lowpass filter.

Description

This example shows a spectral lowpass filter being applied to the image with a 61 depth boxcar. This cube has 256 bands so 61 takes in over a fifth. Although no averaging is done within a single band, the averaging of the pixels of many bands will cause some averaging and smoothing of the image if there is much difference between bands. In this case a blurry image begins to show through.

Command Line

speclowpass from=/work1/mboyd/CM_1514302573_1.cub to=/work1/mboyd/postlow.cub bands=61
This example will filter the image using 61 bands and no limits on high or low.

GUI Screenshot

This program's GUI

Example GUI

Screenshot of the GUI with parameters set to perform the spechighpass filter with a 61 band boxcar on the image CM_1514302573_1.ir.cub.

Input Image

The image graph before the filter

Input image spectral graph before speclowpass filter

Parameter Name: FROM

This is the spectral plot of the center point of the image, (32, 32), and shows all bands, 1- 256. No averaging has been applied, this is clear partialy because of th extreme peaks visible in the first half. The peaks are related to values which differ significantly from the bands around them.

Output Image

The image graph after the filter

Output image spectral graph after being filtered

Parameter Name: TO

This is the image after the filter. As is very clear, the averaging has turned sharp peaks into a smooth slope and small bumps into nothing. All bands in the image are now muchmore similar to each ohter than they were before. Also note that the scale has changed significantly.

History

Stacy Alley2008-09-02 Original version
Mackenzie Boyd2009-06-09 Modified documentation, added exception handling for too many bands, modified examples