https://www.mdu.se/

mdu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Satellite Image Compression Guided by Regions of Interest
KTH Royal Institute of Technology, Sweden.
KTH Royal Institute of Technology, Sweden.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Unibap AB, Sweden.ORCID iD: 0000-0002-8785-5380
Unibap AB, Sweden.
Show others and affiliations
2023 (English)In: Sensors, E-ISSN 1424-8220, Vol. 23, no 2, article id 730Article in journal (Refereed) Published
Abstract [en]

Small satellites empower different applications for an affordable price. By dealing with a limited capacity for using instruments with high power consumption or high data-rate requirements, small satellite missions usually focus on specific monitoring and observation tasks. Considering that multispectral and hyperspectral sensors generate a significant amount of data subjected to communication channel impairments, bandwidth constraint is an important challenge in data transmission. That issue is addressed mainly by source and channel coding techniques aiming at an effective transmission. This paper targets a significant further bandwidth reduction by proposing an on-the-fly analysis on the satellite to decide which information is effectively useful before coding and transmitting. The images are tiled and classified using a set of detection algorithms after defining the least relevant content for general remote sensing applications. The methodology makes use of the red-band, green-band, blue-band, and near-infrared-band measurements to perform the classification of the content by managing a cloud detection algorithm, a change detection algorithm, and a vessel detection algorithm. Experiments for a set of typical scenarios of summer and winter days in Stockholm, Sweden, were conducted, and the results show that non-important content can be identified and discarded without compromising the predefined useful information for water and dry-land regions. For the evaluated images, only 22.3% of the information would need to be transmitted to the ground station to ensure the acquisition of all the important content, which illustrates the merits of the proposed method. Furthermore, the embedded platform’s constraints regarding processing time were analyzed by running the detection algorithms on Unibap’s iX10-100 space cloud platform.

Place, publisher, year, edition, pages
MDPI , 2023. Vol. 23, no 2, article id 730
Keywords [en]
change detection, cloud detection, image compression, satellite communication, vessel detection, Bandwidth, Communication satellites, Infrared devices, Remote sensing, Satellite communication systems, Signal detection, Detection algorithm, Images compression, Region-of-interest, Regions of interest, Satellite communications, Satellite images, Small-satellite
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-61799DOI: 10.3390/s23020730ISI: 000918751400001Scopus ID: 2-s2.0-85146609639OAI: oai:DiVA.org:mdh-61799DiVA, id: diva2:1735226
Available from: 2023-02-08 Created: 2023-02-08 Last updated: 2023-02-15Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Bruhn, Fredrik

Search in DiVA

By author/editor
Bruhn, Fredrik
By organisation
Embedded Systems
In the same journal
Sensors
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 22 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf