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ISIS Documentation
lineeq
This program will normalize a cube based on line averages.
This program will normalize a cube based on line averages.
This is useful for linescan camera images where the signal drifts over time. It can also
be used for correcting for photometric changes when part of the image was taken during the day and
the other part was taken at night.
The boxcar size should be somewhere between 0% and 200%, where 200% will give you the same image back
and 0% will remove all albedo and clean up all noise. The reason for the boxcar size being 200% is because the boxcar
folds at the border, meaning at line zero it's only incorporating 50% of the lines and at the center it's incorporating all of them. The
200% boxcar makes every pixel incorporates a boxcar of all of the data, causing only negligable change in the equation.
The normalization is achieved by collecting all of the line averages for any given band. A lowpass filter
is then run on these averages. Finally, the lines are normalized with their smoothed average. The
CSV output option will output a CSV file (readable by most spreadsheet programs such as Excel)
with the line averages before and after smoothing. Using this data, graphing the line averages will
reveal and identify problem data.
Fixed bug where batchlists failed after a few runs
Steven Lambright
2007-12-11
Fixed problem with gaps in the images causing the program to fail
Steven Lambright
2008-05-13
Removed references to CubeInfo
Debbie A. Cook
2011-11-18
Made the output pixel match the input pixel when the input was a
special pixel
Parameters
Files
Specify the cube to be normalized.
Type
cube
File Mode
input
Specify the output (normalized) cube.
Type
cube
File Mode
output
Specify the CSV file to output the line averages to.
Type
filename
File Mode
output
Internal Default
No Output
Filter
*.csv
Settings
When overriding the default boxcar size, you can enter the new value as a percentage of the image height
or as an absolute size.
Type
string
Default
NONE
Option List:
Option
Brief
Description
NONE
The boxcar size will be computed automatically
The boxcar size will be 10% (rounded up if even).
Exclusions
BOXSIZE
ABSOLUTE
Enter the boxcar size in lines
The boxcar size will be exactly what you enter. No computations will be done.
Inclusions
BOXSIZE
PERCENTAGE
Enter the boxcar size in percentages
This is the percent of the height of the image the boxcar size will be.
Inclusions
BOXSIZE
This will override the default boxcar size when smoothing the line averages. The larger this size is, the less the image is affected.
The smaller the boxcar, the larger the effect. If entering an absolute line size, it must be odd (any even number will automatically be
rounded up).
Type
integer
Output a CSV formatted file of the line averages and the smoothed averages.
Type
boolean
Default
false
Inclusions
CSV
Example 1
Normalizing a cube
This shows how to normalize a cube using this program. The input is valid data with introduced noise.
Command Line
This is the command line to run this program, with a small boxcar, on input.cub.
This screen shot shows how to run this program using a small boxcar on
input.cub.
Input Images
Noise
Noise
Parameter Name:
FROM
This shows the noise that was introduced into the input image. It's values change line by line. This was introduced to input.cub by using fx and adding to the valid data.
Original Data
Original
Parameter Name:
FROM
This is the original image, before anything was done to it.
Input Data
Before
Parameter Name:
FROM
This is the original image with the noise added in.
Output Image
Output Image
After
Parameter Name:
TO
This shows the image after this program was run. Notice the image data is restored, but all albedo was lost.
Example 2
Identifying a problem cube
This program does not properly handle all cubes. When the line averages spike, this program smoothes them,
but bad data could cause these spikes and this program will try to correct bad data incorrectly inthe areas with the spikes.
Command Line
This is the command line to run this program, with a small boxcar, on I07762023RDR_CN.norm.cub and output a CSV file.
Running this program on I07762023RDR_CN.cub with CSV output
Running this program
Parameter Name:
TO
This screen shot shows how to run this program on
I07762023RDR_CN.cub and output the line averages as CSV.
Input Images
CSV Graph
Overall Graph
Parameter Name:
CSV
This shows the graph of the averages from the CSV file. Notice there is a large spike on the far left hand side of the data. This should be investigated further.
CSV Graph (a closer look)
Zoomed In Graph
Parameter Name:
CSV
This shows the graph of the averages from the CSV file zoomed into the left side. Notice the smoothed average (pink) is significantly off from the averages (blue).
This tells us that the data in this region did not normalize properly.
The cube
Input
Parameter Name:
FROM
This shows the first 1000 lines of the image before this program was run. Notice the bright area in this data corrosponds to the spike on the CSV graph.
Output Image
Output Image
Output
Parameter Name:
TO
This shows the first 1000 lines of the image after this program was run. Notice the resulting effects of this incorrect normalization. A smaller boxcar would
balance this area, except for the lines with the bad data, but would also destroy any valid albedo.
Example 3
Deciding on a boxcar size
This shows how the boxcar size affects the output of this program.
Command Line
This is the command line to run this program in this example, where ?? becomes a relative boxcar size.
Running this program on input.cub with a 5% boxcar size
Running this program at 5% boxcar
Parameter Name:
BOXSIZE
This screen shot shows how to run this program using a 5% boxcar on input.cub.
Running this program on input.cub with a 20% boxcar size
Running this program at 20% boxcar
Parameter Name:
BOXSIZE
This screen shot shows how to run this program using a 20% boxcar on input.cub.
Running this program on input.cub with a 50% boxcar size
Running this program at 50% boxcar
Parameter Name:
BOXSIZE
This screen shot shows how to run this program using a 50% boxcar on input.cub.
Input Image
Input Data
Noise
Parameter Name:
FROM
This is the original image. Notice it's very bright at the top and very dark at the bottom.
Output Images
Output Image
Very Small Boxcar
Parameter Name:
TO
This shows the image after this program was run with a very small boxcar. Notice the loss of albedo.
Output Image
Small Boxcar
Parameter Name:
TO
This shows the image after this program was run with a small boxcar. Notice less of the data was properly normalized and there's more albedo.
Output Image
Larger Boxcar
Parameter Name:
TO
This shows the image after this program was run with a larger boxcar. The albedo change from the last example to this one is minimal, but much more data was lost.
