Snapshot hyperspectral imaging Fourier transform spectropolarimeter

E. J. Youngs; M. W. Kudenov

doi:10.1117/12.2273866

7 September 2017 Snapshot hyperspectral imaging Fourier transform spectropolarimeter

E. J. Youngs, M. W. Kudenov

Proceedings Volume 10407, Polarization Science and Remote Sensing VIII; 1040704 (2017) https://doi.org/10.1117/12.2273866
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

Abstract

The design and experimental results of a snapshot spatially heterodyned imaging Fourier transform (SHIFT) spectropolarimeter are presented. The sensor utilizes common-path interferometry, which lends improved compactness and ruggedness over free-space interferometric techniques. The polarization-dependency of the optical instrument can also be leveraged to obtain both spectral and polarimetric measurements. In this paper, calibration procedures and the SHIFT data processing algorithms are described. A data-reduction matrix is utilized to transform the measured per-pixel interferograms into corresponding Stokes parameters. Using this matrix, neural networks are trained to automate the transformation process from measurement to Stokes parameters. Finally, preliminary experimental results of the SHIFT’s ability to distinguish certain spectral signatures are demonstrated.

Conference Presentation

Citation Download Citation

E. J. Youngs and M. W. Kudenov "Snapshot hyperspectral imaging Fourier transform spectropolarimeter", Proc. SPIE 10407, Polarization Science and Remote Sensing VIII, 1040704 (7 September 2017); https://doi.org/10.1117/12.2273866

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available