July 27, 2022, 1:12 a.m. | Joshua Mitton, Simon Peter Mekhail, Miles Padgett, Daniele Faccio, Marco Aversa, Roderick Murray-Smith

cs.CV updates on arXiv.org arxiv.org

We develop a new type of model for solving the task of inverting the
transmission effects of multi-mode optical fibres through the construction of
an $\mathrm{SO}^{+}(2,1)$-equivariant neural network. This model takes
advantage of the of the azimuthal correlations known to exist in fibre speckle
patterns and naturally accounts for the difference in spatial arrangement
between input and speckle patterns. In addition, we use a second
post-processing network to remove circular artifacts, fill gaps, and sharpen
the images, which is required …

arxiv effects networks optics physics

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