Earth Observation (EO) systems are generating an ever-increasing amount of data to be handled on board yet with limited resources, which sometimes hinders a full exploitation of the information content. In this paper, we present a demonstrator of a super-resolved compressive imager operating in whiskbroom mode in the Visible-Near Infrared (VISNIR) and Medium Infrared (MIR) spectral ranges. The demonstrator, which is under development in the frame of the EU H2020 funded SURPRISE project, is based on the use of a Digital MicroMirror Device (DMD) as a core element of its architecture and it is inspired by a single-pixel camera in order to avoid the use of large focal plane arrays. The demonstrator has 10 channels in the VNIR and two channels in the MIR and it can reach a super-resolution factor from 4 x 4 to 32 x 32, that is the ratio between the number of pixels of the image reconstructed at the end of the process and the number of pixels of the detector. Besides, on the grounds of the results obtained by image reconstruction tests on simulated datasets by using Deep Learning based algorithms, data are expected to be natively compressed with a Compression Ratio up to 50%. The study is expected to provide valuable insight for the future development of a novel class of EO instruments with improved performances in terms of ground sampling distance, native compression and on-board processing capabilities. Additional presentation content can be accessed on the supplemental content page.

Super-resolved compressive demonstrator for Earth Observation applications in the Medium Infrared: instrumental concept, optical design and expected performances

Raimondi Valentina
;
Baldi Massimo;Gonnelli Andrea;Guzzi Donatella;Lastri Cinzia;Marzi Emiliano;Nardino Vanni;Palombi Lorenzo;
2023

Abstract

Earth Observation (EO) systems are generating an ever-increasing amount of data to be handled on board yet with limited resources, which sometimes hinders a full exploitation of the information content. In this paper, we present a demonstrator of a super-resolved compressive imager operating in whiskbroom mode in the Visible-Near Infrared (VISNIR) and Medium Infrared (MIR) spectral ranges. The demonstrator, which is under development in the frame of the EU H2020 funded SURPRISE project, is based on the use of a Digital MicroMirror Device (DMD) as a core element of its architecture and it is inspired by a single-pixel camera in order to avoid the use of large focal plane arrays. The demonstrator has 10 channels in the VNIR and two channels in the MIR and it can reach a super-resolution factor from 4 x 4 to 32 x 32, that is the ratio between the number of pixels of the image reconstructed at the end of the process and the number of pixels of the detector. Besides, on the grounds of the results obtained by image reconstruction tests on simulated datasets by using Deep Learning based algorithms, data are expected to be natively compressed with a Compression Ratio up to 50%. The study is expected to provide valuable insight for the future development of a novel class of EO instruments with improved performances in terms of ground sampling distance, native compression and on-board processing capabilities. Additional presentation content can be accessed on the supplemental content page.
2023
Istituto di Fisica Applicata - IFAC
Inglese
Proc. SPIE 12777, International Conference on Space Optics -ICSO 2022
International Conference on Space Optics -- ICSO 2022, 2022, Dubrovnik, Croatia
12777
9781510668034
http://www.scopus.com/record/display.url?eid=2-s2.0-85174055976&origin=inward
03-07/10/2022
COMPRESSIVE SENSING
EARTH OBSERVATION
OPTICAL PAYLOAD
MEDIUM INFRARED
27
restricted
Raimondi, Valentina; Baldi, Massimo; Berndt, Dirk; Bianchi, Tiziano; Gallego Guzmán, Borque; Borrelli, Donato; Carlà, Roberto; Corti, Chiara; Corti, F...espandi
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
   SUper-Resolved comPRessive InStrument in the visible and medium infrared for Earth observation applications
   SURPRISE
   H2020
   870390
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/450916
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