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On-board Satellite Data Processing to Achieve Smart Information Collection
KTH Royal Institute of Technology, Stockholm, 100 44, Sweden.
KTH Royal Institute of Technology, Stockholm, 100 44, Sweden.
KTH Royal Institute of Technology, Stockholm, 100 44, Sweden.
Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system. Unibap AB, Kungsängsgatan 12, Uppsala, 753 22, Sweden.ORCID-id: 0000-0002-8785-5380
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2022 (Engelska)Ingår i: Proceedings of SPIE - The International Society for Optical Engineering, SPIE , 2022, Vol. 12138Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Nowadays, it is a reality to launch, operate, and utilize small satellites at an affordable cost. However, bandwidth constraint is still an important challenge. For instance, multispectral and hyperspectral sensors generate a significant amount of data subjected to communication channel impairments, which is addressed mainly by source and channel coding aiming at an effective transmission. This paper targets a significant further bandwidth reduction by proposing an on-the-fly analysis technique on the satellite to decide which information is effectively useful for specific target applications, before coding and transmitting. The challenge would be detecting clouds and vessels having the measurements of red-band, green-band, blue-band, and near infrared band, aiming at sufficient probability of detection, avoiding false alarms. Furthermore, the embedded platform constraints must be satisfied. Experiments for typical scenarios of summer and winter days in Stockholm, Sweden, are conducted using data from the Mimir’s Well, the Saab AI-based data fusion system. Results show that non-relevant content can be identified and discarded, pointing out that for the cloudy scenarios evaluated, up to 73.1% percent of image content can be suppressed without compromising the useful information into the image. For the water regions in the scenarios containing vessels, results indicate that a stringent amount of data can be discarded (up to 98.5%) when transmitting only the regions of interest (ROI).

Ort, förlag, år, upplaga, sidor
SPIE , 2022. Vol. 12138
Nyckelord [en]
Cloud detection, Image compression, Satellite communication, Vessel detection
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URN: urn:nbn:se:mdh:diva-59541DOI: 10.1117/12.2620955ISI: 000943943400017Scopus ID: 2-s2.0-85132990951ISBN: 9781510651524 (tryckt)OAI: oai:DiVA.org:mdh-59541DiVA, id: diva2:1681246
Konferens
Optics, Photonics and Digital Technologies for Imaging Applications VII 2022
Tillgänglig från: 2022-07-06 Skapad: 2022-07-06 Senast uppdaterad: 2023-04-12Bibliografiskt granskad

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