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Nature Communications· 2019Q1

Transmission of natural scene images through a multimode fibre

Piergiorgio Caramazza, Oisín Moran, Roderick Murray-Smith, Daniele Faccio

Short summary

A new method statistically reconstructs the inverse transformation matrix of a multimode fiber, enabling real-time, high-resolution, full-color imaging of natural scenes, overcoming limitations of previous approaches.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Developed a statistical method to reconstruct the inverse transformation matrix of a multimode fiber.
  • Demonstrated real-time, high-resolution, full-color imaging of natural scenes through the fiber.
  • Overcame limitations of previous methods that required full complex field control or were restricted to specific image classes.
  • The technique shows general-purpose imaging capability, unlike prior approaches.

AI-generated from the title and abstract; the full text is not read.

Abstract

The optical transport of images through a multimode fibre remains an outstanding challenge with applications ranging from optical communications to neuro-imaging. State of the art approaches either involve measurement and control of the full complex field transmitted through the fibre or, more recently, training of artificial neural networks that however, are typically limited to image classes belong to the same class as the training data set. Here we implement a method that statistically reconstructs the inverse transformation matrix for the fibre. We demonstrate imaging at high frame rates, high resolutions and in full colour of natural scenes, thus demonstrating general-purpose imaging capability. Real-time imaging over long fibre lengths opens alternative routes to exploitation for example for secure communication systems, novel remote imaging devices, quantum state control processing and endoscopy.

The authors' abstract, as published at the source. Nature Communications, 2019 · DOI ↗

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Field: Acoustics and Ultrasonics

Acoustics and UltrasonicsPhysics and Astronomy