Imaging with phase diversity: simulations with a neural network

Nancy A. Miller; Alice V. Ling

doi:10.1117/12.142052

1 April 1993 Imaging with phase diversity: simulations with a neural network

Nancy A. Miller, Alice V. Ling

Proceedings Volume 1982, Photoelectronic Detection and Imaging: Technology and Applications '93; (1993) https://doi.org/10.1117/12.142052
Event: Photoelectronic Detection and Imaging: Technology and Applications '93, 1993, Beijing, China

Abstract

The technique of phase diversity was proposed for estimating telescope aberrations for an unknown extended object. The original version of phase diversity requires extensive processing due to a nonlinear optimization algorithm which is prohibitive in a real-time system. Therefore, neural networks were explored as an alternative solution of the problem and this paper shows the modification of the traditional phase diversity method to employ neural networks to estimate aberrations of point source and extended scene data. Simulations indicated aberrations could be estimated to an average error of 0.02 waves rms.

Citation Download Citation

Nancy A. Miller and Alice V. Ling "Imaging with phase diversity: simulations with a neural network", Proc. SPIE 1982, Photoelectronic Detection and Imaging: Technology and Applications '93, (1 April 1993); https://doi.org/10.1117/12.142052

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