Super-resolution in disordered media using neural networks

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View a PDF of the paper titled Super-resolution in disordered media using neural networks, by Alexander Christie and 5 other authors

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Abstract:We propose a methodology that exploits large and diverse data sets to accurately estimate the ambient medium’s Green’s functions in strongly scattering media. Given these estimates, obtained with and without the use of neural networks, excellent imaging results are achieved, with a resolution that is better than that of a homogeneous medium. This phenomenon, also known as super-resolution, occurs because the ambient scattering medium effectively enhances the physical imaging aperture. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

Submission history

From: Alexei Novikov [view email]
[v1]
Mon, 28 Oct 2024 21:35:08 UTC (795 KB)
[v2]
Wed, 30 Oct 2024 17:27:58 UTC (795 KB)
[v3]
Fri, 8 Nov 2024 05:35:04 UTC (795 KB)
[v4]
Tue, 3 Dec 2024 22:39:45 UTC (1,025 KB)



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