Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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

compressive sensing --- lensless imaging --- Diffusercam --- Ingénierie, informatique & technologie > Ingénierie aérospatiale

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Compressed sensing (Telecommunication) --- Biosensing Techniques --- Medical innovations. --- Innovations, Medical --- Medicine --- Medical technology --- Technological innovations --- Compressive sensing (Telecommunication) --- Sensing, Compressed (Telecommunication) --- Sparse sampling (Telecommunication) --- Signal processing --- Innovations

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Compressed sensing is an emerging field that allows for the recovery of a sparse signal from fewer measurements than permitted by the Nyquist theorem. This new paradigm can be used to create new imager architectures that are simpler, more compact, and cheaper than traditional imagers, acquiring images in a compressed manner and thereby reducing the amount of data to handle. These characteristics are appealing for potential implementation in Earth observation satellites, where size and weight are critical factors, and where the amount of collected data is substantial, with limited storage capacity and transfer rates to the ground.
This master’s thesis focuses on the implementation of the optical part of a compressive sensing imager in the laboratory, with the objective of performing a particular compressive sensing reconstruction method, known as inpainting. A comprehensive review of the state of the art in compressive sensing and various imager architectures is first provided. Afterwards, the design of the instrument and the selection of all its components are extensively detailed. A digital micromirror device is used for producing incomplete, damaged images of a scene, and a camera detector records the resulting image. Subsequently, a calibration procedure for the damaged images was established to prepare them for reconstruction through inpainting. This calibration includes dark and fl at frame corrections, as well as post-reconstruction image perspective correction. The instrument’s point spread function is also measured, and a dithering method is implemented to improve its resolution. Furthermore, the pattern mask used for the reconstruction is studied and calibrated using morphological erosion.

compressive sensing --- inpainting --- optical imaging device --- digital micromirror device --- Scheimpflug principle --- pattern mask --- point spread function --- dithering --- Ingénierie, informatique & technologie > Ingénierie aérospatiale

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Optical fiber communication --- Compressed sensing (Telecommunication) --- Quality control. --- Compressive sensing (Telecommunication) --- Sensing, Compressed (Telecommunication) --- Sparse sampling (Telecommunication) --- Signal processing --- Fiber-optic communication --- Fiber optic telecommunication --- Optical communications --- Fiber optics

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Quantum optics has received a lot of attention in recent decades due to the handiness and versatility of optical systems, which have been exploited both to study the foundations of quantum mechanics and for various applications. In this Special Issue, we collect some articles and a review focusing on some research activities that show the potential of quantum optics in the advancement of quantum technologies.

Research & information: general --- Physics --- integrated photonics --- quantum optics --- quantum simulation --- mesoscopic quantum states of light --- nonclassical photon-number correlations --- lossy transmission channels --- quantum state engineering --- nonlinear interferometer --- spontaneous four-wave mixing --- quantum message authentication --- quantum three-pass protocol --- Gao's forgery --- swap test --- conditional states --- silicon photomultipliers --- optical cross-talk --- nonclassicality --- quantum imaging --- plenoptic imaging --- quantum correlations --- SPAD arrays --- quantum fisher information --- compressive sensing --- quantum finite automata --- periodic languages --- confidence amplification --- photodetection --- integrated photonics --- quantum optics --- quantum simulation --- mesoscopic quantum states of light --- nonclassical photon-number correlations --- lossy transmission channels --- quantum state engineering --- nonlinear interferometer --- spontaneous four-wave mixing --- quantum message authentication --- quantum three-pass protocol --- Gao's forgery --- swap test --- conditional states --- silicon photomultipliers --- optical cross-talk --- nonclassicality --- quantum imaging --- plenoptic imaging --- quantum correlations --- SPAD arrays --- quantum fisher information --- compressive sensing --- quantum finite automata --- periodic languages --- confidence amplification --- photodetection