From b3d4edd4801156beaab02eee6b1241218852fc9e Mon Sep 17 00:00:00 2001 From: Stuart Sides Date: Thu, 19 Nov 2020 16:13:05 -0700 Subject: [PATCH] Added text to description by Dave Humm. Closes #3860 (#4107) * Added text to description by Dave Humm. Closes #3860 * Forgot to add to the change log file * Update after review * Updated after review --- CHANGELOG.md | 1 + isis/src/lro/apps/lronaccal/lronaccal.xml | 95 +++++++++++++++++------ isis/src/lro/apps/lrowaccal/lrowaccal.xml | 50 +++++++++++- 3 files changed, 120 insertions(+), 26 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index b011334587..0bc189ec98 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -29,6 +29,7 @@ update the Unreleased link so that it compares against the latest release tag. --> ## [Unreleased] + - Added documentation to lronaccal and lrowaccal to describe why there are negative DNs in I/F calibrated images. - Fixed so required files are reported instead of continuing without them. [#4038](https://github.com/USGS-Astrogeology/ISIS3/issues/4038) diff --git a/isis/src/lro/apps/lronaccal/lronaccal.xml b/isis/src/lro/apps/lronaccal/lronaccal.xml index a4ddd2fcee..e7f718ed9e 100644 --- a/isis/src/lro/apps/lronaccal/lronaccal.xml +++ b/isis/src/lro/apps/lronaccal/lronaccal.xml @@ -8,44 +8,89 @@

- lronaccal performs radiometric corrections to images acquired by the Narrow Angle - Camera aboard the Lunar Reconnaissance Orbiter spacecraft. The LRO NAC camera - will make observations simulteously with the HiRise camera. + 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 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. + 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. + 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. + 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.
+

+ +

+ 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. +

diff --git a/isis/src/lro/apps/lrowaccal/lrowaccal.xml b/isis/src/lro/apps/lrowaccal/lrowaccal.xml index f8aefc3cae..6439ed8fa3 100644 --- a/isis/src/lro/apps/lrowaccal/lrowaccal.xml +++ b/isis/src/lro/apps/lrowaccal/lrowaccal.xml @@ -15,7 +15,7 @@

- Corrections are applied in the following order: Dark, Flat-field, Radiometric, Special pixel mask, and Temperature. + Corrections are applied in the following order: Dark, Flat-field, Radiometric, Special pixel mask, and Temperature.

Dark Correction:

@@ -149,6 +149,54 @@ If TEMPRATUREFILE is not set, the constants are loaded from $lro/calibration/WAC_TempratureConstants.????.pvl

+ +

+ 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.
+

+ +

+ 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. +

+