Products > Thermal Imaging
High resolution thermal cores for sUAS
Hyper_Spectral:
We currently use IR imagery for locating equipment defects with sUAS and the FLIR XT. It's my understanding that the XT and XT2 are essentially the TAU 2 core made by FLIR.
Great, so our current best integration option is a 640x512 radiometric camera on a gimbal with <30mK sensitivity. We've come a long way, but I want more resolution.
Producing quality thermal orthomosaics without significant user input correction to the processing is the ultimate goal here and for that we need more resolution
I see mostly resolutions below our current spec discussed here, but there has to be more right? What other cores are on the market that should we be looking for in the <10lb range and resolution higher than 640x512?
P.S. what's all this opto-mechanical microscan magical resolution doubling feature I'm reading about? It sounds promising, but there's not a lot of discussion on it. I assume a true high res core is better than a core claiming the same resolution while utilizing the "doubling" technology
Vipitis:
at 640x512@30hz and radiometric you are already way at the top.
There are higher resolution uncooled detectors, only a few. The very highest resolution uncooled sensor is a TWV1912 made by Fairchild/BAE - and to my knowledge there is one available camera build around it by Sierra Olympic, the Vayu HD. While I was able to hold myself back from asking them about the price, I am expecting it to be in the 30k range.
But implementation will be much more difficult, eventhough they market it for airborne use, it does not produce the radiometric flir images that some photogrammetry apps now support. I would ask for a demo, if you are in such a position where they answer your and workout the software workflow with help from the developers of whatever software you are currently using, if they offer specelized solution.
Any kind of airborne detector that is cooled, can have even higher resolutions, these are normally build for police helicopters, or military aircraft and focus on target tracking, range indication and high zoom levels and less radiometric data for mosaics.
Is superresolution the thing you talk about? It normally works on a camera that is in about the same place and takes 4 images in short succession and using the hand wiggle or wind to move the sensor by a fraction of a pixel resulting in a single high resolution image when combined. In photogrammetry you have a point cloud, where every point is based on data gathered, to get better resolution, just gather more points by flying over the same section from a different angle and direction. In theory there are many ways to interpolate more data points based on the seemingly random intervals you have with your reconstruction when making up a wavelet direction. But I have yet to read about it in detail. I am not sure how advanced software is in the field, but using a visible light camera to create the pointcloud gives you more data points due to the high resolution, if possible a solid model could be reconstructed and the thermal pixels projected onto them. Giving you a "3D MSX" dataset.
Chanc3:
sUAS and thermal imaging cameras basically describes my career! There are higher resolution cameras out there, but you won't find many theatre radiometric. Is that a requirement?
They're not that big, but not much has been done to develop them into a usable system on drones.
TooQik:
These might be worth a look:
https://ipi-infrared.com.au/product/keii-hl-1024-uav-special-module/
http://en.keii.com.cn/index.php/Product/detail/paretn_id/0/cat_id/14/goods_id/27#path
I have no idea on quality, cost etc though. Others here might be able to provide better examples.
Hyper_Spectral:
--- Quote from: Vipitis on February 19, 2019, 08:29:10 pm ---at 640x512@30hz and radiometric you are already way at the top.
There are higher resolution uncooled detectors, only a few. The very highest resolution uncooled sensor is a TWV1912 made by Fairchild/BAE - and to my knowledge there is one available camera build around it by Sierra Olympic, the Vayu HD. While I was able to hold myself back from asking them about the price, I am expecting it to be in the 30k range.
But implementation will be much more difficult, eventhough they market it for airborne use, it does not produce the radiometric flir images that some photogrammetry apps now support. I would ask for a demo, if you are in such a position where they answer your and workout the software workflow with help from the developers of whatever software you are currently using, if they offer specelized solution.
Any kind of airborne detector that is cooled, can have even higher resolutions, these are normally build for police helicopters, or military aircraft and focus on target tracking, range indication and high zoom levels and less radiometric data for mosaics.
Is superresolution the thing you talk about? It normally works on a camera that is in about the same place and takes 4 images in short succession and using the hand wiggle or wind to move the sensor by a fraction of a pixel resulting in a single high resolution image when combined. In photogrammetry you have a point cloud, where every point is based on data gathered, to get better resolution, just gather more points by flying over the same section from a different angle and direction. In theory there are many ways to interpolate more data points based on the seemingly random intervals you have with your reconstruction when making up a wavelet direction. But I have yet to read about it in detail. I am not sure how advanced software is in the field, but using a visible light camera to create the pointcloud gives you more data points due to the high resolution, if possible a solid model could be reconstructed and the thermal pixels projected onto them. Giving you a "3D MSX" dataset.
--- End quote ---
Thank you for providing that information, I've put in requests for information from both Fairchild and Sierra imaging.
Superresolution doesn't sound quite like what they're referring to, but it's definitely possible it's just a marketing wank version of superresolution. There was a research article on it, but I seem to have misplaced the link. You can find the brochure here:
https://www.infratec-infrared.com/downloads/en/thermography/flyer/vc-hd/infratec-variocam-hd-b-mail-en.pdf
Your last paragraph is very close to the current "standard" post-processing we see, but let me explain for the sake of everyone interested in this topic.
Right now there are two key pieces of software used in the sUAS mapping industry, Pix4D and Agisoft Photoscan. They use different algorithms, to my understanding, but they're probably pretty close in technique at this point. Pix4D is probably the most common, though. This is thanks mostly due to it's massive improvement in the last 2-3 years. The point clouds and orthomosaics produced from RGB imagery we're getting now versus just a year or two ago are drastically different and much better. Thermal datasets are also much better, but they still suck. Bad. This is mostly due to the differences in resolution in my opinion. A 4000x3000 image is much easier to match to another 4000x3000 image. Matching 640x512 imagery has to be difficult. Most of the orthomosaics you see produced are made with 90/90 overlap at high altitudes sacrificing final GSD. We want a final GSD of 5cm/px (100-150' AGL with the XT 13mm lens) while ~10cm/px GSD is much more reasonable when you consider the post-processing capabilities and time requirements for simply collecting the data. Consider the flight time is 3-4x the time at less overlap. These problems ultimately lead to a "product," but not without significant input into Pix4D (manually creating tie points between the RGB point cloud and thermal imagery). Poor final GSD, high time investment in flights and processing, and a poor final product are what we see in the thermal post-processed data world right now. Sure, you can do it. But it's not worth it, imo.
Flying over the same area multiple times probably would help with matching and the point cloud, but it's the same thing as adding more overlap (in a less efficient manner) and it doesn't equate to the realm of LiDAR where I do see a need for densifying point clouds. LiDAR is another topic a little further down the road for us.
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