Energy Efficient Approximate 3D Image Reconstruction

We demonstrate an efficient and accelerated parallel, sparse depth reconstruction framework using compressed sensing (compressed sensing (CS)) and approximate computing. Employing data parallelism for rapid image formation, the depth image is reconstructed from sparsely sampled scenes using convex o...

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Veröffentlicht in:	IEEE transactions on emerging topics in computing 2022-10, Vol.10 (4), p.1854-1866
Hauptverfasser:	Wu, Yun, Asmann, Andreas, Stewart, Brian D., Wallace, Andrew M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Approximate computing Arithmetic Compressed sensing Computational geometry Convex analysis convex optimisation Convexity depth reconstruction Field programmable gate arrays FPGA Image reconstruction Laser radar LiDAR Linear algebra Optimization parallel computing Photonics Power consumption Power management Sensors Three-dimensional displays
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