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Proceedings Paper

Compressive sensing optical coherence tomography using randomly accessible lasers
Author(s): Mark Harfouche; Naresh Satyan; Arseny Vasilyev; Amnon Yariv
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Paper Abstract

We propose and demonstrate a novel a compressive sensing swept source optical coherence tomography (SSOCT) system that enables high speed images to be taken while maintaining the high resolution offered from a large bandwidth sweep. Conventional SSOCT systems sweep the optical frequency of a laser ω(t) to determine the depth of the reflectors at a given lateral location. A scatterer located at delay τ appears as a sinusoid cos (ω(t)τ ) at the photodetector. The finite optical chirp rate and the speed of analog to digital and digital to analog converters limit the acquisition rate of an axial scan. The proposed acquisition modality enables much faster image acquisition rates by interrogating the beat signal at randomly selected optical frequencies while preserving resolution and depth of field. The system utilizes a randomly accessible laser, a modulated grating Y-branch laser, to sample the interference pattern from a scene at randomly selected optical frequencies over an optical bandwidth of 5 THz , corresponding to a resolution of 30 μm in air. The depth profile is then reconstructed using an l1 minimization algorithm with a LASSO constraint. Signal-dependent noise sources, shot noise and phase noise, are analyzed and taken into consideration during the recovery. Redundant dictionaries are used to improve the reconstruction of the depth profile. A compression by a factor of 10 for sparse targets up to a depth of 15 mm in noisy environments is shown.

Paper Details

Date Published: 23 May 2014
PDF: 8 pages
Proc. SPIE 9109, Compressive Sensing III, 91090L (23 May 2014); doi: 10.1117/12.2048754
Show Author Affiliations
Mark Harfouche, California Institute of Technology (United States)
Naresh Satyan, Telaris, Inc. (United States)
California Institute of Technology (United States)
Arseny Vasilyev, California Institute of Technology (United States)
Amnon Yariv, California Institute of Technology (United States)

Published in SPIE Proceedings Vol. 9109:
Compressive Sensing III
Fauzia Ahmad, Editor(s)

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