Scientists have historically been very skeptical about automated region-of-interest cropping, or fancy novelty-detection methods, or even certain kinds of compression. They are always afraid that something of importance will be filtered out. It's a difficult argument to win.
Prioritized downlink is accepted (you still get everything, but there's some automation that finds the most interesting stuff and sends it first).
There's even experimental acceptance of planning/machine vision systems that choose targets opportunistically while a rover is moving from point A to point B.
That is, points A and B were chosen by science planners. But while the robot is moving from A to B, it looks at stuff and stops en route to collect more data if it sees something interesting. You can sell this to scientists because they still get the data from points A and B (they're in control) but they also get more data from in-between, that might be interesting, and that they would not get otherwise.
This has been used on Opportunity and won the NASA software of the year award last year (http://www.jpl.nasa.gov/news/news.cfm?release=2011-380). It's a harder problem than it sounds like, because the robot has to re-plan its activities on-the-fly ("plan" in the sense of moving cameras, turning the robot, etc.)
Prioritized downlink is accepted (you still get everything, but there's some automation that finds the most interesting stuff and sends it first).
There's even experimental acceptance of planning/machine vision systems that choose targets opportunistically while a rover is moving from point A to point B.
That is, points A and B were chosen by science planners. But while the robot is moving from A to B, it looks at stuff and stops en route to collect more data if it sees something interesting. You can sell this to scientists because they still get the data from points A and B (they're in control) but they also get more data from in-between, that might be interesting, and that they would not get otherwise.
This has been used on Opportunity and won the NASA software of the year award last year (http://www.jpl.nasa.gov/news/news.cfm?release=2011-380). It's a harder problem than it sounds like, because the robot has to re-plan its activities on-the-fly ("plan" in the sense of moving cameras, turning the robot, etc.)