Searched for: author%3A%22Mosk%2C+Allard+P.%22
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Seifert, Jacob (author), Shao, Y. (author), Mosk, Allard P. (author)
Computational imaging is increasingly vital for a broad spectrum of applications, ranging from biological to material sciences. This includes applications where the object is known and sufficiently sparse, allowing it to be described with a reduced number of parameters. When no explicit parameterization is available, a deep generative model...
journal article 2024
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Seifert, Jacob (author), Shao, Y. (author), van Dam, Rens (author), Bouchet, Dorian (author), van Leeuwen, Tristan (author), Mosk, Allard P. (author)
Optical measurements often exhibit mixed Poisson–Gaussian noise statistics, which hampers the image quality, particularly under low signal-to-noise ratio (SNR) conditions. Computational imaging falls short in such situations when solely Poissonian noise statistics are assumed. In response to this challenge, we define a loss function that...
journal article 2023
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Akbulut, Duygu (author), Strudley, Tom (author), Bertolotti, Jacopo (author), Bakkers, E.P.A.M. (author), Lagendijk, Ad (author), Muskens, Otto L. (author), Vos, Willem L. (author), Mosk, Allard P. (author)
We demonstrate that optical transmission matrices (TMs) provide a powerful tool to extract the photonic strength of disordered complex media, independent of surface effects. We measure the TM of a strongly scattering GaP nanowire medium and compare the singular value density of the measured TM to a random-matrix-based wave transport model. By...
journal article 2016