Continuing on with the string of GlobalOrtho stories, image capture, both aerial and terrestrial, is, just like operating a robot car, an outdoor sport.
At the heart of the GlobalOrtho project was the UltraCam-G. Designed and built by our team in Graz Austria. Something like 200 MP, taking simultaneous RGB, Monochrome, and NIR images at 30cm resolution for the RGB image. And this camera was tested. Countless flights over Graz and the surrounding areas. Calibrated for physical construction, lens distortion, thermal drift, chromatic aberration and anything else the designers could come up with. The pictures were stunning. The 3D modeling was amazing. Not just 2.5D shells, but full 3D models with undercuts and holes. So we sent it out into the field.
And the feedlots were purple. The edges of the images were red. As I mentioned the other day there were spikes and holes. How could this have happened? These cameras were tested. Over and over again. And all the tests came back great. We sent one back for recalibration, but the before and after results showed no change, and the test images were spot on.
So we kept digging. And we realized a few things. Color balance. It turns out that Graz and the surrounding areas are Austrian Alps (who would have guessed). Lots of alpine forests and orange tiled roofs. And the software did great in those areas. But there aren't a lot of feedlots. And color correction was done in a lab. Yes, we used sunlight equivalent lighting, but the room was a few meters deep. Outside there were cloudy days, dusty days, humid days, and in some places smoggy days. Plus, the camera flew at 5000m, and with a +/-40° FOV, the amount of air between the camera and the ground was very different between the center of the image and the edge.
Geometry. Lots of church steeples and building corners. But no miles square corn fields with waving stalks. Or pastures with walking cows. Or large lakes. Or high rise urban cores with deep canyons. Lots of environments that weren't part of the test set. And the software struggled.
Why, because even though we captured hundreds of thousands of test images, and ran hundreds of test jobs. they were all basically the same operational domain. For all the hours we spent testing, we really only ran a few tests. Then we got out into the real world and the situations were different. So we had to evolve. Make things more dynamic and adaptive. Because that's the way the world is.