Computer Science – Performance
Scientific paper
Mar 2012
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012p%26ss...62..153t&link_type=abstract
Planetary and Space Science, Volume 62, Issue 1, p. 153-159.
Computer Science
Performance
Scientific paper
Previous missions have imaged active plumes at Io and Enceladus, as well as outgassing by cometary nuclei. It is often difficult to predict where and when these transient events will occur, so characterizing them requires collecting long image sequences with many redundant frames. This demands a prohibitive fraction of the spacecraft's limited cache and bandwidth, and precludes sustained surveys of plume activity. Onboard processing could enable long-term plume monitoring campaigns with high imaging rates. Specifically, spacecraft can analyze image sequences onboard to identify plumes, with events triggering preferential storage, prioritized transmission, or follow up with coincident observations by Thermal or Visible Near-Infrared imagers. We propose a detection method based on horizon identification with Random Sample Consensus (RANSAC). The approach evidences reliable performance on a test set of plume images from Enceladus and Io.
Bünte Melissa
Castano Rebecca
Chien Steve
Greeley Ronald
Thompson David R.
No associations
LandOfFree
Image processing onboard spacecraft for autonomous plume detection does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Image processing onboard spacecraft for autonomous plume detection, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Image processing onboard spacecraft for autonomous plume detection will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1058213