Paper Info
Title
Optical Compressive Imaging Technologies for Space Big Data
Abstract
The increasing amount of data generated by space applications poses several challenges due to limited resources available onboard: power, memory, computation, data rate. In this paper, we propose Compressed Sensing (CS) as the key tool to face those challenges via compressive imaging. This signal processing technique, only recently applied to space applications, dramatically simplifies the image acquisition featuring native compression/encryption and enabling onboard image analysis, allowing to design simpler and lighter optical systems. In this paper, we try to answer the following question: To what extent are the potential benefits of CS going to materialize in a realistic “space big data” application scenario? To this purpose, we first review compressive imaging techniques and already existing prototypes and concepts, critically discussing the technological issues involved. Then, we propose a set of instrument concepts in the application domains of space science, planetary exploration and earth observation, most suitable for a CS-based application. For the most promising of them, we go deeper into the analysis showing preliminary reconstruction performance tests.
Year
DOI
Venue
2020
10.1109/TBDATA.2019.2907135
IEEE Transactions on Big Data
Keywords
DocType
Volume
Compressed sensing,big data,space applications,compressive imaging,hyperspectral imaging,spatial light modulators,detectors,earth observation,space science,planetary exploration
Journal
6
Issue
ISSN
Citations 
3
2332-7790
0
PageRank 
References 
Authors
0.34
0
13
Name
Order
Citations
PageRank
Giulio Coluccia1427.20
Cinzia Lastri2504.28
Donatella Guzzi3143.26
Enrico Magli41319114.81
Vanni Nardino5121.86
Lorenzo Palombi621.11
Ivan Pippi723.09
valentina raimondi821.78
Chiara Ravazzi911413.23
Florin Garoi1000.68
Coltuc, Daniela1131.09
Raffaele Vitulli12214.88
Alessandro Zuccaro Marchi1300.68