Single image super-resolution via regularized extreme learning regression for imagery from microgrid polarimeters

Garrett C. Sargent; Bradley M. Ratliff; Vijayan K. Asari

doi:10.1117/12.2273945

30 August 2017 Single image super-resolution via regularized extreme learning regression for imagery from microgrid polarimeters

Garrett C. Sargent, Bradley M. Ratliff, Vijayan K. Asari

Author Affiliations +

Proceedings Volume 10407, Polarization Science and Remote Sensing VIII; 104070C (2017) https://doi.org/10.1117/12.2273945
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

Abstract

The advantage of division of focal plane imaging polarimeters is their ability to obtain temporally synchronized intensity measurements across a scene; however, they sacrifice spatial resolution in doing so due to their spatially modulated arrangement of the pixel-to-pixel polarizers and often result in aliased imagery. Here, we propose a super-resolution method based upon two previously trained extreme learning machines (ELM) that attempt to recover missing high frequency and low frequency content beyond the spatial resolution of the sensor. This method yields a computationally fast and simple way of recovering lost high and low frequency content from demosaicing raw microgrid polarimetric imagery. The proposed method outperforms other state-of-the-art single-image super-resolution algorithms in terms of structural similarity and peak signal-to-noise ratio.

Conference Presentation

Citation Download Citation

Garrett C. Sargent, Bradley M. Ratliff, and Vijayan K. Asari "Single image super-resolution via regularized extreme learning regression for imagery from microgrid polarimeters", Proc. SPIE 10407, Polarization Science and Remote Sensing VIII, 104070C (30 August 2017); https://doi.org/10.1117/12.2273945

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