Snapshot temporal compressive microscopy using an iterative algorithm with untrained neural networks

Document Type

Article

Publication Date

4-15-2021

Abstract

We report a snapshot temporal compressive microscopy imaging system, using the idea of video compressive sensing, to capture high-speed microscopic scenes with a low-speed camera. An untrained deep neural network is used in our iterative inversion algorithm to reconstruct 20 high-speed video frames from a single compressed measurement. Specifically, using a camera working at 50 frames per second (fps) to capture the measurement, we can recover videos at 1000 fps. Our deep neural network is embedded in the inversion algorithm, and its parameters are learned simultaneously with the reconstruction.

Identifier

85102675286 (Scopus)

Publication Title

Optics Letters

External Full Text Location

https://doi.org/10.1364/OL.420139

e-ISSN

15394794

ISSN

01469592

PubMed ID

33857096

First Page

1888

Last Page

1891

Issue

8

Volume

46

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