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Satellite Image Com...
Satellite Image Compression Guided by Regions of Interest
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- Schwartz, Christofer (author)
- KTH,KTH Royal Institute of Technology, Sweden
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- Sander, Ingo, Professor, 1964- (author)
- KTH,Elektronik och inbyggda system,KTH Royal Institute of Technology, Sweden
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- Bruhn, Fredrik (author)
- Mälardalens universitet,Inbyggda system,Unibap AB, Kungsangsgatan 12, S-75322 Uppsala, Sweden.;Mälardalen Univ, Sch Innovat Design & Engn IDT, Embedded Syst Div, POB 883, S-72123 Västerås, Sweden.
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- Persson, M. (author)
- Unibap AB, Kungsangsgatan 12, S-75322 Uppsala, Sweden.
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- Ekblad, J. (author)
- Saab AB, Olof Palmes Gata 17, S-11122 Stockholm, Sweden.
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- Fuglesang, Christer, 1957- (author)
- KTH,Partikel- och astropartikelfysik,KTH Royal Institute of Technology, Sweden
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(creator_code:org_t)
- 2023-01-09
- 2023
- English.
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In: Sensors. - : MDPI. - 1424-8220. ; 23:2
- Related links:
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https://doi.org/10.3...
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https://urn.kb.se/re...
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Abstract
Subject headings
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- 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.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Keyword
- 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
Publication and Content Type
- ref (subject category)
- art (subject category)
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