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Juno perijove 6, May 19, 2017
Gerald
post Jun 17 2017, 11:06 PM
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Thanks! That's currently on rank 4 of my planned Juno activities. I'll probably just invalidate these patches, and reconstruct the missing color channel by the color of the immediate environment. Fixing this is on my plan since more than a year. I hope, that early next week, I'll get it implemented.
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Sean
post Jun 21 2017, 09:22 AM
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Some image processing & retiming tests on Gerald's animation for perijove 06...

Click thru each image for a video









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Bjorn Jonsson
post Jun 22 2017, 11:49 PM
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I have been running into an interesting issue when processing some of the images. Here is an example, an enhanced crop from image PJ06_119:

Attached Image


The arrows point in the direction of a color discontinuity. The color change at left is because of a drop in the green intensity to the right of the discontinuity and the color change at right (which is more subtle) is because of a drop in the red intensity. These color changes are not a real feature (I verified this by checking image PJ06_118 which also shows this area).

As a sanity check I checked Gerald's images and this also appears there. It occurred to me that this might be a consequence of how the images are decompanded. In the original, raw image the intensity near the color change is ~210 in both cases (green and red). Keeping this in mind the companding table is rather interesting. Below are a few lines from the table. The columns are 8-bit_SQROOT_Value, 12-bit_Linear_Value and the change from the previous value in the 12 bit column.

207 1375 16
208 1391 16
209 1407 16 <---
210 1439 32 <---
211 1471 32
212 1503 32

Note that the difference between adjacent values jumps from 16 to 32. Of course this is normal but I strongly suspect that this creates visual artifacts (and maybe the human visual system also exaggerates the difference because of a Mach band effect or something similar).

I plan on exploring this further to see if I'm right (I'm not yet completely sure). I may even experiment with a slightly modified companding table. Strictly speaking this would result in slightly less accurate images where the intensity is ~210 but aesthetically they would look better if I'm successful.

I'm interesting in knowing if someone else (Gerald?) has also explored this issue.
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Gerald
post Jun 23 2017, 08:46 AM
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I've noticed this before, but I didn't yet narrow it down to a candidate cause as good as yours. Before the decompanding table became available, I've run an empirical / statistical analysis on the red/green and blue/green quotients as a function of the green value, and found smoothed curves where the decompanding function has kinks between linear fragments. I attributed this to a smoothing effect caused by my analysis method. But with your observation, it might be worth to run a new analysis with formally decompanded values. I did so when I used the decompanding table for the first time, and it looked so much better than before, that I was happy, and didn't persue this any further.
When preparing for my EPSC talk about Jupiter's reflectance function (finally accepted!), and haze, I'll take another very close look at the effect of solar incidence angle and emission angle on brightness and color. I'd think, that any errors in the decompanding function should show up as anomalies.

Btw, Seán, your processing tests are really very! promising.
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mcaplinger
post Jun 23 2017, 04:59 PM
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QUOTE (Bjorn Jonsson @ Jun 22 2017, 03:49 PM) *
I'm interesting in knowing if someone else has also explored this issue.

Since the companding maps all input values from 1392 to 1407 to 209 (for example) there's no way to uniquely recover the input, obviously. This is more obvious for Junocam where the companding is done in a piecewise linear fashion and there is a slope change at 209-210 (in contrast to MSL where a smoother full table is used). At various times people have talked about intentionally adding gaussian noise back into the decompanded values, but I've never tried this. Depending on where in the processing flow you do the decompanding relative to other operations (photometric removal, for example) and what precision you are doing this to, you may or may not be quantizing the values further.


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Disclaimer: This post is based on public information only. Any opinions are my own.
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Bjorn Jonsson
post Jun 26 2017, 10:57 PM
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Here is the first of three sets of images that I recently finished processing. This is image PJ06_113. First an approximately true color/contrast version. Small scale features have been sharpened a bit, mainly to compensate for all of the resampling during the many processing steps:

Attached Image
Attached Image

Attached Image


And a version with enhanced color and contrast and where the sharpness has been further increased. The effects of global illumination have also been removed to increase the visibility of dimly lit features not far from the terminator.

Attached Image

Attached Image
Attached Image


The image scale is identical to the image scale of the original data. Three images are shown instead of one; with Juno very close to Jupiter a single 'global' image would look distorted unless you're *very* close to the screen. This is a very high resolution observation. The resolution at the nadir (slightly below center in the image where the limb isn't visible) is ~3.5 km/pixel.

And finally, per Emily's suggestion earlier in the thread here is the most relevant metadata from the metadata file associated with this image:

IMAGE_TIME = 2017-05-19T05:55:32.040
MISSION_PHASE_NAME = PERIJOVE 6
PRODUCT_ID = JNCE_2017139_06C00113_V01
SPACECRAFT_ALTITUDE = 5110.4 km
SPACECRAFT_NAME = JUNO
SUB_SPACECRAFT_LATITUDE = 24.5356
SUB_SPACECRAFT_LONGITUDE = 136.3498
TITLE = POI: The Big Red Stripe
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Bjorn Jonsson
post Jun 26 2017, 11:03 PM
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And here is image PJ06_118. First a true color version:

Attached Image
Attached Image
Attached Image


And an exaggerated version:

Attached Image

Attached Image
Attached Image


And a subset from the relevant metadata:

IMAGE_TIME = 2017-05-19T06:13:08.855
MISSION_PHASE_NAME = PERIJOVE 6
PRODUCT_ID = JNCE_2017139_06C00118_V01
SPACECRAFT_ALTITUDE = 10053.0 km
SPACECRAFT_NAME = JUNO
SUB_SPACECRAFT_LATITUDE = -25.7077
SUB_SPACECRAFT_LONGITUDE = 148.3166
TITLE = POI: Belt-Zone border
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Bjorn Jonsson
post Jun 26 2017, 11:14 PM
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Image PJ06_119, the true color version:

Attached Image
Attached Image

Attached Image


An exaggerated version:

Attached Image

Attached Image
Attached Image


This is in my opinion one of JunoCams's more spectacular observations because of the brown barge. The barge is located at latitude ~40 degrees south. The color reminds me of when I saw Jupiter through a telescope during Christmas back in 2002 in exquisite seeing - by far the best I have ever experienced. There was almost no turbulence, the image was very steady and the colors deeper and stronger than I have ever seen since. One of the features visible was something looking like a brown barge. It had a deep and strong reddish-brownish color. The color of the barge in these JunoCam images remind me of the colors I saw back in 2002. One caveat though: Human 'color memory' is notoriously unreliable.

Metadata:

IMAGE_TIME = 2017-05-19T06:15:39.862
MISSION_PHASE_NAME = PERIJOVE 6
PRODUCT_ID = JNCE_2017139_06C00119_V01
SPACECRAFT_ALTITUDE = 12857.7 km
SPACECRAFT_NAME = JUNO
SUB_SPACECRAFT_LATITUDE = -31.5873
SUB_SPACECRAFT_LONGITUDE = 150.0307
TITLE = POI's: Carl Sagan's Jawbreaker, South Tropical Zone (STrZ)
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Bjorn Jonsson
post Jun 26 2017, 11:20 PM
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There is very helpful information by John Rogers on JunoCam's perijove-6 observations at https://www.britastro.org/node/10479

At the bottom is a map showing the location/context for all of the hi-res perijove-6 images. It was even tempting to post the map here but I decided to only post the link - there's a lot of interesting information there in addition to the context map.
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Sean
post Jun 30 2017, 11:21 AM
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A humble reply to Bjorn's amazing work...

PJ06_121 from Gerald's batch, flipped & processed.


Attached Image


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Gerald
post Jul 2 2017, 04:27 PM
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QUOTE (Bjorn Jonsson @ Jun 17 2017, 10:23 PM) *
I have noticed colored 'dots' in some of your images/maps that are there because the original framelets contain some dark 'spots' ...

Finally, I found some time to continue working on this topic. Here the hot pixels for the rgb filters during the early PJ06 approach phase in the order of the framlets in the raws, first the actual mask, then linear stretched by factors 2, 4, 8, and 16:
x1:
Attached Image

x2:
Attached Image

x4:
Attached Image

x8:
Attached Image

x16:
Attached Image

The mask is derived from raw TDI-1 Perijove-06 approach RGB images JNCE_2017132_05C00592 to 614.

Identifying the hot pixels plays a role, when looking for events, like energetic particle hits, lightnings or impacts. A general point noise filter would risk to filter out such bright events. Long-term monitoring of hot pixels may serve as kind of a radiation dosimeter.

Next, I'll have a try with the dark spots.
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Gerald
post Jul 2 2017, 06:19 PM
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Here preliminary masks for the "blemish" on the RGB filters, based only on pj6, #111 and #112:
Attached Image

Attached Image

I've implemented the software a few years ago, so forgot the exact meaning of the brightness values. But when comparing the masks with the raws, you'll notice the more or less subtle darkening in the raws where the masks are bright.
Due to the TDI, the masks are stretched vertically a little bit.
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Gerald
post Jul 11 2017, 06:58 PM
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In the meanwhile, I'm merging dark spots with hot pixels into this mask in order to invalidate raw pixels:
Attached Image

The spots are larger than the actual bad pixels. But e.g. due to compression artifacts, pixels surrounding the bad pixels can be involved. And I've included even pixel, which appear imperfect in only a subtle way.

This is pj06 #133 without patching:
Attached Image


This is my current state of a patched version:
Attached Image


And these are the spots, I've tried to patch:
Attached Image

They are derived from the above mask, and show the color to be patched.

If framelets of the same channel overlap for a target position, and the according pixel is invalid in one framelet, the valid pixel of the other framelet is chosen.
Else, the applied algorithm currently tries to patch only those pixles that are bad in exactly one color channel.
It uses a "good" channel, and adds the invalid one by deriving color from nearby pixles of similar brightness.
In rare cases, this can add new artifacts, but I think the result is significantly better than without patching. I may persue these rare cases later, and add some sanity constraints.
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Sean
post Jul 11 2017, 07:46 PM
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Great work Gerald. Will this resolve the blue dots on the animations also?


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Gerald
post Jul 11 2017, 08:24 PM
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Yes, I'm expecting so. Of course, this applies only to future renditions. At least, it's in time for PJ7 renditions, and maybe for reviews of PJ6 and before.
Seamless blending between scenes made from two or more different raws is an interesting challenge I've still to work on, especially when trying to render realistic scenes from outside the original s/c trajectory.
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