False colour composites were something I was introduced to in high school GIS and did a lot of in undergrad remote sensing. It was one of those Eureka! moments for me in terms of developing a better understanding of signals and signal processing, as well as sensors and data collection. Ie. absorbing the reality that the way in which my eyes (or any optical sensor) see the world is not canonical. Vegetation is red, not green!
It was also just the COOLEST THING EVER to swap infrared bands in LANDSAT ETM+ imagery and watch vegetation immediately pop out at you. It's what turned this sort of dull (at least for a teenager) geoscience into a kind of puzzle where you have to figure out how to bring the signal up out of the data.
And, insects see flowers (and each other) differently than we do, as they are senstive to different parts of the spectrum, specfically ultraviolet. They see patterns and markings that are not discernable to human eyes.
It's really fun to play with black and white photography using various kinds of color filters and see how different you can get the same scene to appear.
> Ie. absorbing the reality that the way in which my eyes (or any optical sensor) see the world is not canonical. Vegetation is red, not green!
Pretty funny to figure out that your perspective wasn't objective reality and then immediately decide to canonicalize another arbitrary reality as the One True Reality.
I interpreted that step as "once you click 'Auto Input Levels', drag the center triangle of the 3 at the bottom of the histogram to where you think the median of the histogram is". That middle slider defaults to being the midpoint of the other 2 sliders. I'm not sure if there is a smarter way to move it to the median beyond "looks about right".
I got this as a result https://i.imgur.com/RsXx3y2.jpeg and it certainly doesn't preserve the color of the rest of the image (there are probably more algorithmic steps needed for that) but it does seem to make highlight the same faint patterns much more clearly.
The levels tool maps a subset of the channel range to the full range, effectively changing the brightness and contrast in one step.
The center point controls the gamma correction, so you can map a biased distribution (mostly bright or dark for example) to be more evenly distributed.
That was the purpose of that step - move the midpoint slider to about where the peak in the histogram is, to get an evenly distributed range.
The low/high slider can be moved towards that to increase the contrast.
"Contrast" here will only apply to the A/B channels, which is the color information, so it's increasing the color contrast and unbiasing it, while keeping the luminance information.
Photoshop also can do the same transform, and interactively in the LAB colorspace (no need to combine/uncombine the channels first).
“No one really knows why people made the rock art they made, at least in many cases,” Harman said
Well, it's obvious they really wanted to though. This isn't like marking on a wall with a Sharpie. They had to work at it to make it happen. The commitment alone is impressive even if it was just a "Grogg was here!"
I tried to look for hidden rock art at Ankgor Wat by imaging with multiple bandpass filters and amplifying cross-spectral differences. I didn't succeed, but maybe I was in the wrong place. The shit guards there also didn't like me using a tripod while I changed filters, so it was also hasty.
If it makes you feel any better, I've also never had any luck finding hidden rock art, petroglyphs, or similar using multispectal bandpass filters or decorellation stretching.
I was super excited about DCS based on some of the recovered petroglyph photos online, and integrated it into some software I wrote years ago.[1] Still hoping I find something as interesting with it as the fellow mentioned in the article. It works, but I haven't had a "gosh, I never would have seen that without DCS!" moment.
"In this paper, we review the theory behind decorrelation stretch and propose some alternative algorithms that resolve the issues of the standard approach."
"A contribution is mandatory before I will send the plugin. It may take me a few days to respond, have patience.
Please note that the plugin is not an app. It has much more functionality than is possible in an app on a smartphone."
"The DStretch [mobile] app is a lightweight version of DStretch intended to give users the ability to enhance rock art in the field. It is not a substitute for the DStretch plugin which has much more functionality."
In reality very interesting work and results, but a little disturbing that it took three or four decades and a self-funded citizen scientist to transfer the knowledge to the application.
https://spinoff.nasa.gov/Manipulating_Satellite_Photos_Now_R...
It was also just the COOLEST THING EVER to swap infrared bands in LANDSAT ETM+ imagery and watch vegetation immediately pop out at you. It's what turned this sort of dull (at least for a teenager) geoscience into a kind of puzzle where you have to figure out how to bring the signal up out of the data.
(Also fun to play with a polarizing filter.)
Pretty funny to figure out that your perspective wasn't objective reality and then immediately decide to canonicalize another arbitrary reality as the One True Reality.
1) Colors > Components > Decompose > LAB
2) For the layers of the A/B (chroma) channels, Colors > Levels > "Auto Input Levels" (maximize the contrast), and move the mid point to the median.
3) Colors > Components > Compose > LAB
The result I got for the original mars image was a washed out red image with some yellow around the craters.
I got this as a result https://i.imgur.com/RsXx3y2.jpeg and it certainly doesn't preserve the color of the rest of the image (there are probably more algorithmic steps needed for that) but it does seem to make highlight the same faint patterns much more clearly.
The center point controls the gamma correction, so you can map a biased distribution (mostly bright or dark for example) to be more evenly distributed.
That was the purpose of that step - move the midpoint slider to about where the peak in the histogram is, to get an evenly distributed range.
The low/high slider can be moved towards that to increase the contrast.
"Contrast" here will only apply to the A/B channels, which is the color information, so it's increasing the color contrast and unbiasing it, while keeping the luminance information.
Photoshop also can do the same transform, and interactively in the LAB colorspace (no need to combine/uncombine the channels first).
This is what I was after: "move the midpoint slider to about where the peak in the histogram is, to get an evenly distributed range."
It kinda worked! Thank you and sorry for making you explain the gory details though they are appreciated and useful.
Well, it's obvious they really wanted to though. This isn't like marking on a wall with a Sharpie. They had to work at it to make it happen. The commitment alone is impressive even if it was just a "Grogg was here!"
> "No matter what you do, when we find something weird in ancient history we will decide it must've been part of a fertility rite."
I was super excited about DCS based on some of the recovered petroglyph photos online, and integrated it into some software I wrote years ago.[1] Still hoping I find something as interesting with it as the fellow mentioned in the article. It works, but I haven't had a "gosh, I never would have seen that without DCS!" moment.
[1] https://www.beneaththewaves.net/Photography/Decorrelation_St... / https://www.beneaththewaves.net/Software/The_Mirrors_Surface...
https://youtu.be/ONZcjs1Pjmk https://youtu.be/_qtzWNZApsw
This paper might also be of interest - https://www.mdpi.com/2227-7390/13/20/3297
"In this paper, we review the theory behind decorrelation stretch and propose some alternative algorithms that resolve the issues of the standard approach."
https://dstretch.com/Apps/index.html
"The DStretch [mobile] app is a lightweight version of DStretch intended to give users the ability to enhance rock art in the field. It is not a substitute for the DStretch plugin which has much more functionality."
In reality very interesting work and results, but a little disturbing that it took three or four decades and a self-funded citizen scientist to transfer the knowledge to the application.