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Comment by kevin_thibedeau | Hacker News Reader

These are pushbroom linear sensors stacked up in the focal plane. The spectral channels are physically separated by larger distance than neighboring pixels in a Bayer grid. There is a time delay between each channel sweeping over the same location that gets corrected when the final imagery is aligned. The moving plane at altitude violates assumption of a static scene and exposes the scanning behavior.

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The B2 bomber photo isn't from a push boom sensor, because it would be distorted since it's moving relative to the camera. This would manifest itself as a shear along the motion vector . There is no shear in this photo, only spectral bands.

I've spent a number of years doing image orthorectification, and satellite imagery post-processing, then also worked on Google Earth and Google Maps, so I can tell you precisely what happened. This is a satellite image from a satellite which photographs different spectra at different times. There isn't enough parallax at typical orbital distance for this much displacement to come from multiple cameras. Looking at some parked cars, this looks like 20-30cm resolution per pixel, which is consistent with the newer earth imaging satellites.

Google Earth made a blog post about this a while ago (https://www.gearthblog.com/blog/archives/2015/03/planes-flig...)

Shame we don't know what the delay between spectra is, would be fun to work out how fast the plane is traveling.

I've seen larger aberrations from satellite captures of planes. But I've no idea how to estimate height or speed by that.

You can get height if you can find the shadow, and find the time that the photo was taken, because at any given time and date, you can compute sun position, and you know the precise lat/lng of the shadow. The shadow would need to be in the same photo, though. (actually, it's a bit to the northwest, just found it).

If you can find a vertical structure, like an antenna mast, you can measure shadow length and direction and if you know the height of the antenna, you have enough information for some trigonometry.

Speed is harder. You'd need to know the difference between exposures.

Aha! Here we go. Here's a telephone pole: https://earth.google.com/web/search/39.0303298,-93.58495/@39...

We know that telephone poles stick about 32 feet from the ground. Measuring the shadow in Google Earth above, it's about 20 feet. Now, it's a simple ratio.

Using Earth, I measured the distance from the plane to its shadow at about 2430 feet, that would put it at 3,900ft, which is surprisingly low, but I don't know the height of that pole for sure. It's the right ballpark, though.

Not too low if landing? From another comment:

> This one was probably on final approach during the summer when the winds are usually out of the south and was probably about 2,000 feet above the ground.

https://news.ycombinator.com/item?id=29628167

Probably headed to Whiteman AFB. Here's one parked: https://www.google.com/maps/place/38%C2%B043'29.7%22N+93%C2%...

The B2 is based out of Whiteman AFB near Warrensburg, MO so roughly 25 miles or 40 km south of where the plane is so it is probably on its final approach to land or just took off.

For those interested, here is the shadow: https://www.google.com/maps/place/39%C2%B001'28.8%22N+93%C2%...

Took me a while to find it, so thought I'd save someone else the scrolling/search cost.

Thanks! It's conveniently hidden by a grassy area and some trees which throw shadows of their own. Actually, I should be doing something more useful at the moment...

Agree it wouldn’t be parallax from multiple cameras on the same satellite but the delay between images seems quite short for physical filter swapping (~20ms per filter).

(Edit: Actually DLP does it in about that amount of time, nvm)

If it’s anything like space telescopes there are more than 3 spectral filters that can be selected which rules out a static Bayer-type filter system.

For anyone wondering about what a pushboom sensor is - http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.72....

Basically a 1D sensor that acquires a 2D image because the camera itself is moving.

In this case, I'd imagine that there are 3 such sensors for RGB.

FWIW, depending on the satellite (this one is probably WorldView 3), there usually more like ~6-7 channels in the visible.

It makes for easier top-of-atmosphere correction, and can be useful for things other than pretty pictures.

Is CMOS a type of pushboom sensor?

CMOS is a manufacturing method for integrated circuits.

Any type of sensor could be CMOS.

Thanks for answering!

I haven't seen a CCD CMOS, yet, and I don't _think_ microbolometers are CMOS-based (and wouldn't be surprised if no one publically tried). Happy to see some exotic examples, though. Those are always intriguing the hacker curiosity.

Most CMOS imaging sensors in digital cameras do scan, but not like a push-broom sensor. The push-broom sensor only has a single line of pixels that physically moves (or that something moves across), like in a scanner or a photocopier. But as others have said, those sensors might also be fabricated with CMOS technology.

Whereas your normal digital camera has a fixed rectangular array of pixels, and the scanning is just reading them progressively (what's called 'rolling shutter') because it's hard to read them all quickly enough at once. Some more expensive sensors do 'global shutter' which usually has better motion characteristics for video.

> Basically a 1D sensor that acquires a 2D image because the camera itself is moving.

Or a static camera and a moving subject. This same style of camera is used for "photo finishes" in races. The camera is literally the finish line, and the the first pixel to "cross the line" is the winner.

Also office scanners. Basically, it's still a 2D image, but instead of two spatial dimensions, it has a spacial dimension and a time dimension.

Is the R/G/B separation greater because these sensors are built like TDI CCD lines?

edit: Seems like pushbroom is the name for TDI when it's put in a satellite.

Exactly! I'm working on some stuff now to exploit this very effect, the small time difference in the bands can be used to find velocities of moving objects.

This is incredibly cool. What's the application (if it's possible to obscure whatever details you don't want to divulge)?

Its coastal physics work, you can infer near shore conditions by watching wave propagation.

So... like where submarines are based on water disturbances?

That's not what I'm doing but it seems possible you could watch refraction patterns and tell that there are submerged objects, but you'd need to know the water depth without that object there, as there'd be no great way to tell if the object is a submarine or a pile of sand. Also, most of these satellites pass over fairly rarely so wouldn't be super useful for tracking things that move. I'm mostly interested in finding the piles of sand :)

The same effect can be used to estimate cloud heights, and to identify aircraft flying above clouds.

Parallax based Cloud Detection for Sentinel-2 Analysis Ready Data Generation https://www.researchgate.net/publication/332999809_Parallax_...

Aircraft Detection above Clouds by Sentinel-2 MSI Parallax https://www.mdpi.com/2072-4292/13/15/3016

Is this at all analogous to how we used red/blue shift to determine the speed at which astronomical objects are moving towards/away from us?

No, that’s the Doppler effect. This is a time delay between when different colors were captured.

Ah gotcha. Makes sense. Thanks!

So... does anyone have a tool handy to correct the frames?

Better yet... does anyone have the corrected image?

I must say there is quite some beauty in the choice and structure of words here.

Funnily enough, I thought exactly the same when reading the parent post ! Grateful to be in such well-spoken company :)

I think modern satellites have matrix sensors

It depends on the satellite. Weather satellites in GEO do because they aren't moving relative to the surface and they have time constraints for scanning the full earth disc. Higher resolution imaging satellites use linear sensors. However, they use TDI imaging which at a low level makes them superficially like an area array with limited vertical resolution but the light collection is still fundamentally different.

I don’t think this is the case as we don’t see any rolling shutter distortion. The linear sensor scans just like a shutter curtain exhibiting the same distortion. The plane is proportioned correctly. Maybe the scan time is fast enough.

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