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lronacecho

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Removes echo effects from a LRO NAC image

Overview Parameters Example 1

Description

lronacecho implements a correction designed to remove an echo effect from LROC NAC images. In the summer of 2011, an echo effect was discovered in the NAC detectors. The signal in each pixel is replicated to a smaller extent in the pixel on the same line 2 columns over, 1 collumn in summed NACs. MSSS was consulted and it was confirmed this is a detector effect related to the high speed (>3000 lines/second) of the NAC detectors. The even and odd columns of the detector have separate signal processing chains, so when one pixel is read out, the next pixel with the same signal processing chain is two columns over. There is no measurable effect 4 columns over; the echo has no echo.

The size of the echo effect was determined by analyzing the signal at the edge the detector mask on each side of many NAC images, and by analyzing images with stars that had well-defined ghosts offset by two pixels. The effect is large enough that an inverse technique is needed to correct it with sufficient accuracy. The analysis determined that the echo is a larger percent of the signal for signals less than 100 DN. However, the correction uses a fixed fraction equal to for all pixels of all images. This value was derived from many flight images and is optimized for signals greater than 100 DN. Using a larger echo fraction for lower DN values would degrade the signal-to-noise too much. To reduce any artifacts in the begining of the image, the SMOOTHINGROWS parameter is used to specify the number of visible samples, before the full constant is applied. This fractional delta constant is calculated by the function: for NACLs, with the offset being from 5064 rather than 0 in the NACR.

A brute force inverse technique derived from simple substitution was used early in the development of the echo correction. Let be the NAC-L ideal signal in column i of a line without the echo effect, and the actual signal including the echo effect. Consider an ideal case where the detector response is linear and uniform and we ignore the other calibration corrections. Then

So, we have the line of the actual image , which includes the echo, and we want to recover the ideal image line without the echo. To avoid confusion, let's call this new calculated value where is an approximation of the original dependent on the accuracy of . It's trivial for line 0. Then, for line 2 we just substitute the solution from line 0 for and solve for . Likewise, for line 4 substitute for using line 2 and solve for , etc. The result is

Note, however, that this equivalent to:

So we can calculate the new correction factors from the previously corrected pixels (the ); there is no need to calculate each fractional "echo" factor from the original image (the ).

At the end of the echo correction, the entire image is scaled by a factor of to maintain the radiometric calibration.

In practice it has proven most successful to apply the echo correction after the flat field correction.
The effect of the echo correction on the flat field is not significant.


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History

Jacob Danton2011-11-17 Original version
Adam Licht2013-01-15 Updated default Delta parameter per D. Humm. Added Documentation.
Adam Licht2013-01-25 Updated algorithm to normalize the output cub after preforming the correction, to preserve radiometric calibration.
Adam Licht2013-04-05 Added a new parameter "SMOOTHINGROWS". This specifies the number of samples to slowly ramp up the constant in. Fixed how special pixels were handeled in the normalization step.

Parameter Groups

Files

Name Description
FROM First Input cube
TO Output cube

Parameters

Name Description
DELTA Multiplicative echo constant
SMOOTHINGROWS Number of rows in detector space to slowly increase the delta constant on
X

Files: FROM


Description

Use this parameter to select the cube to correct

Type cube
File Mode input
Filter *.cub
Close Window
X

Files: TO


Description

This file will contain the result of the correction

Type cube
File Mode output
Pixel Type real
Close Window
X

Parameters: DELTA


Description

This defines the multiplicative constant for the echo factor

Type double
Default 0.326
Close Window
X

Parameters: SMOOTHINGROWS


Description

This defines the number of detector samples in the begining of an image before the full correction is reached. Note that in summed images, this number of rows will be divided by two when translated to visible image space. That is: In native images, this parameter's default of 20 detector samples will affect the first 20 visible rows in image space. For summed images, this paramter's default of 20 detector samples will affect the first 10 visible rows in image space.

Type integer
Default 20
Close Window

Example 1

Removing echo from NACL (no summing) image

Description

This example demonstrates the common usage of lronacecho. This is provided to help demonstrate what noise is being affected and the expected results.

Command Line

lronacecho lronacecho from=nacl00020d3a.cal.cub to=nacl00020d3a.cal.echo.cub
Running lronacecho with default DELTA on a calibrated LRO NACL image

GUI Screenshot

Removing echo from nacl00020d3a.cal.cub

Removing echo from nacl00020d3a.cal.cub

This is what the graphical interface should look like in a typical run. The input to lronacecho in this example is nacl00020d3a.cal.cub, a calibrated LRO NACL image with no summing. The resulting image, nacl00020d3a.cal.echo.cub, will have echo effect removed.

Input Image

Input image nacl00020d3a.cal.cub

Input image nacl00020d3a.cal.cub

This is a small area of the input to lronacecho, a calibrated LRO NACL image. The features are slightly blurred due to an echo effect.

Output Images

Output image nacl00020d3a.cal.echo.cub

Output image nacl00020d3a.cal.echo.cub

This is a small area of the output to lronacecho, a calibrated LRO NACL image with echo effects removed. The blurring from the echo effect has been removed.

Blinking between input and output

Blinking between input and output

This is a small area of the input and output to lronacecho, animated to highlght the differences between the images. The output is the sharper image.