Optical Compressive Imaging Technologies for Space Big Data

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.