Faculté des Sciences appliquées
Faculté des Sciences appliquées

Master thesis and internship[BR]- Master's thesis : Study of compressive sensing in view of space imaging applications[BR]- Integration Internship

Gramegna, Sabrina ULiège
Promotor(s) : Georges, Marc ULiège
Date of defense : 27-Jun-2022/28-Jun-2022 • Permalink :
Title : Master thesis and internship[BR]- Master's thesis : Study of compressive sensing in view of space imaging applications[BR]- Integration Internship
Author : Gramegna, Sabrina ULiège
Date of defense  : 27-Jun-2022/28-Jun-2022
Advisor(s) : Georges, Marc ULiège
Committee's member(s) : Habraken, Serge ULiège
Van Droogenbroeck, Marc ULiège
Kirkove, Murielle ULiège
Language : English
Keywords : [en] compressive sensing
[en] lensless imaging
[en] Diffusercam
Discipline(s) : Engineering, computing & technology > Aerospace & aeronautics engineering
Institution(s) : Université de Liège, Liège, Belgique
Degree: Master en ingénieur civil en aérospatiale, à finalité spécialisée en "aerospace engineering"
Faculty: Master thesis of the Faculté des Sciences appliquées


[en] The objective of this work is to use the compressive sensing in the field of the space exploration.
The compressive sensing theory affirms that an image can be retrieved taking only fewer mea-
surement with respect to the minimum number dictated by the Nyquist theory. Contrarily to
the classical method of acquisition of an image, the CS technique allows to create lensless cam-
eras like the Flatcam, the NoRDS-CAIC and the DiffuserCam. The drawback of this technique
is the need of a decoding algorithm for the reconstruction of the original image.
The reconstruction method of the images is not unique, there are classical methods, that use
the total variation minimization, and the deep learning methods. This work analyzes and com-
pares two classical and two deep learning methods in order to find the best method for the
space application.
The simulations have found that the method using the deep learning approach give optimum
results. The images can be well-reconstructed already with a number of measurement that is
the 30% of the size of the images in less than one second.
In order to practically understand the principle of the compressive sensing, an example of the
DiffuserCam has been constructed in the laboratory. The camera is composed only by a diffuser
and a sensor. The experience gave great results, the images have been reconstructed with great
quality in short time.
Finally, the compressive sensing seems to be fascinating for the space application. This tech-
nique allows to suppress the compressing board because the data are taken already compressed.
The suppression of the compression board reduces the mass and especially the power budgets.
Moreover, the post-processing on board allows the reduction of the downlink transmission.
The compressive sensing in space exploration finds its application especially in the infrared
spectral band. In fact, the infrared detectors are too expensive and the compressive sensing
instruments uses the single pixel detectors that are cheaper



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  • Gramegna, Sabrina ULiège Université de Liège > Master ingé. civ. aérospat., à fin.


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