lronaccal performs radiometric corrections to images acquired by the Narrow Angle
Camera aboard the Lunar Reconnaissance Orbiter spacecraft.
The LRO NAC detector has a total of 5064 pixels, divided among an A
channel and a B channel. The pixels alternate between the two channels:
ABABABAB, etc. Images from LROC NAC may or may not include all pixels in the
acquired image. There are special summing modes that are utilized
on-board the spacecraft to average detector pixels to combine them into a
single output pixel value. The value of the ISIS label keyord,
SpatialSumming, indicates the number of samples that were summed and
averaged to result in the pixel values stored in the file. Note that this
will reduce the number of samples in the output image by a factor of at
most the SpatialSumming mode value.
The LROC NAC camera has the ability to acquire images of differing sizes in
both line and sample. The starting hardware detector pixel for the
acquired image is specified by the ISIS label keyword, SampleFirstPixel.
The first pixel in the detector is indicated by a value of 0.
Dark current pixels are taken for each line from the masked pixels
that lie along each edge of the image.
If SpatialSumming is 1 the dark current pixels are averaged together then
this average is subtracted from all image pixels. If SpatialSumming is 2,
the dark current pixels for the A and B channel are averaged separately,
then the A channel dark average is subtracted from the A channel image
pixels and the B channel dark average is subtracted from the B channel
image pixels.
The DN level in an uncalibrated image is the sum of the true signal from the scene,
the bias, the dark current, and random noise in all 3 components. The random noise in
the true signal and dark current is called shot noise and the random noise in the bias
is called read noise. The true signal, bias, and dark current are defined as mean
values so that if the random noise were averaged down to insignificance by taking a
very large number of images and averaging them, the resulting image would be the true
scene, bias, and dark current with no systematic error. That implies the statistical
distribution of the random noise has an average of zero, and therefore the random noise
has both positive and negative values, except for the trivial case of zero random noise.
The calibration equation is:
reportedDN = ObservedDN - MeanBias - DarkCurrent
Where:
ObservedDN = TrueDN + E
E is a randomly sampled value from (mu, sigma^2) and mu=0
TrueDN is the signal that would be reported in an idealized case of an instrument with zero noise.
The dark average produced is dependant on which options are selected.
There are three options for dark calibration/correction. If the image has exposure code of zero,
the nearest dark files with exposure code of zero will be used.
Nearest pair of darks (Default):
This option selects the two closest dark files (before and after the observation) and
computes a time-weighted average. In the ideal case, this average product should characterize
the dynamic dark response the best. Note: Each dark file is an average of a month’s worth of
dark observations under given settings (i.e., exposure code, summing mode, etc.). The maximum
time range between pairs of dark files is 45 days. If a suitable pair is not found, the latest
dark file taken before the image will be used.
pixel_dark_average =
avgDarkLine1_pixel * |darkfile1_time - time| + avgDarkLine2_pixel * |darkfile2_time - time|
/ (1.0 * ( |darkFile1_time - time| + |darkFile2_time - time| ) )
Nearest dark file:
This option selects the nearest dark file (before or after the observations).
This option is typically only used when a pair of darks do not surround the observation.
For example, during the mission, new NACs may not have a dark file in the dark catalog
for times after the observation being calibrated. In this case, lronaccal will use
only the previous NAC dark in the calibration steps. However, suppose the image is calibrated
again after new darks have been added to the catalog. In that case, the default options for
lronaccal will use a pair of dark observations, and the resulting calibrated image may have
slightly different intensities than the NAC processed with only a single dark file.
Note: While this is not a default option, if only one dark is available, lronaccal will
automatically apply the nearest dark file. The user can see which dark(s) were applied in
the cube header.
Custom dark:
This option uses a single custom dark file that the user must supply with the DarkFile parameter.
This option is typically only used in special cases, such as calibrating very long exposure NAC images.
Let's look at the case of a calibrated image for which the true signal
is zero, a dark image. In calibration the mean bias and dark current are
subtracted. The random noise term is then randomly sampled from a known
distribution with a mean of zero. Since the distribution has a mean of
zero, values for the random noise can be positive or negative.
Therefore, the addition of random noise to a pixel with true signal near
zero can result in negative DN values.
Negative reported DNs are possible when E < -1 * TrueDN. These are
pixels in a very dark image that happen to have a strongly negative
random noise value.
Note: ObservedDN and TrueDN both must be greater than or equal to zero.
For ObservedDN, it's because the hardware is not able to report negative
DN values . For TrueDN, it's because radiance and reflectivity cannot be
negative. The dimmest target is one that is completely dark, and for
that target TrueDN = 0.
If run on a non-spiceinited cube, this program requires access to local mission-specific
SPICE kernels, in order to find the distance between the sun and the target body.
When run on a spiceinited cube, this can be determined using the camera model.
Using a spiceinited cube as input has the advantage of not requiring that local
mission-specific kernels be available. (See spiceinit web=true.)
