From Event: SPIE Optical Engineering + Applications, 2016
signal processing methods from software-driven computer engineering and applied mathematics. The compressed
sensing theory in particular established a practical framework for reconstructing the scene content using few linear
combinations of complex measurements and a sparse prior for regularizing the solution. Compressed sensing found
direct applications in digital holography for microscopy. Indeed, the wave propagation phenomenon in free space
mixes in a natural way the spatial distribution of point sources from the 3-dimensional scene. As the 3-dimensional
scene is mapped to a 2-dimensional hologram, the hologram samples form a compressed representation of the
scene as well. This overview paper discusses contributions in the field of compressed digital holography at the
micro scale. Then, an outreach on future extensions towards the real-size macro scale is discussed. Thanks to
advances in sensor technologies, increasing computing power and the recent improvements in sparse digital signal
processing, holographic modalities are on the verge of practical high-quality visualization at a macroscopic scale
where much higher resolution holograms must be acquired and processed on the computer.
Colas Schretter, Stijn Bettens, David Blinder, Béatrice Pesquet-Popescu, Marco Cagnazzo, Frédéric Dufaux, and Peter Schelkens, "Compressed digital holography: from micro towards macro," Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99710V (Presented at SPIE Optical Engineering + Applications: August 30, 2016; Published: 27 September 2016); https://doi.org/10.1117/12.2238761.
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