Algorithmic self-calibration in computational imaging

Laura Waller

doi:10.1364/MATH.2017.MM2C.1

Imaging and Applied Optics 2017 (3D, AIO, COSI, IS, MATH, pcAOP)
OSA Technical Digest (online) (Optica Publishing Group, 2017),
paper MM2C.1
•https://doi.org/10.1364/MATH.2017.MM2C.1

Algorithmic self-calibration in computational imaging

Laura Waller

Mathematics in Imaging 2017

San Francisco, California United States
26–29 June 2017
ISBN: 978-1-943580-29-3

From the session
Computational Imaging (1) (MM2C)

Open Access

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L. Waller, "Algorithmic self-calibration in computational imaging," in Imaging and Applied Optics 2017 (3D, AIO, COSI, IS, MATH, pcAOP), OSA Technical Digest (online) (Optica Publishing Group, 2017), paper MM2C.1.

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Abstract

Computational imaging systems are sensitive to model mismatch errors (e.g. misalignment). We describe new methods that correct for experimental errors within the inverse problem, avoiding calibration. This results in robust and user-friendly setups.

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