Enhancing stability in Zernike coefficient computation through deep learning for polygonal mirrors of electro-optical satellite payloads

Shinwook Kim; Youngchun Youk; Goeun Kim

doi:10.1117/12.3033855

1 November 2024 Enhancing stability in Zernike coefficient computation through deep learning for polygonal mirrors of electro-optical satellite payloads

Shinwook Kim, Youngchun Youk, Goeun Kim

Author Affiliations +

Proceedings Volume 13200, Electro-Optical and Infrared Systems: Technology and Applications XXI; 132001U (2024) https://doi.org/10.1117/12.3033855
Event: Security + Defence, 2024, Edinburgh, United Kingdom

Conference Poster

Abstract

In this study, we analyze the stability of Zernike coefficient computation using deep learning techniques and propose a new training method for deep learning model that can reliably output higher-order Zernike coefficients. Previous studies have shown that deep learning is a powerful tool for accurately deriving the Zernike coefficients of polygonal mirrors, but reliably extracting higher-order Zernike coefficients remains one of the challenges. To overcome these challenges, we present a new training method for the stability of deep learning model, enabling reliable high-order Zernike coefficient computation. The proposed deep learning model is designed based on the Network-in-Network concept, and a two-stage training process ensures that low-order and high-order Zernike coefficients are simultaneously reliably generated. Experimental results for performance evaluation show that the proposed deep learning model is effective in outputting stable and reliable higher-order Zernike coefficients, especially for polygonal mirrors.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shinwook Kim, Youngchun Youk, and Goeun Kim "Enhancing stability in Zernike coefficient computation through deep learning for polygonal mirrors of electro-optical satellite payloads", Proc. SPIE 13200, Electro-Optical and Infrared Systems: Technology and Applications XXI, 132001U (1 November 2024); https://doi.org/10.1117/12.3033855

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