Reconstructing targets based on the enhancement of speckle patterns with the hybrid input-output algorithm

Qianqian Cheng; Enlai Guo; Qianying Cui; Jing Han; Lianfa Bai

doi:10.1117/12.2586639

15 January 2021 Reconstructing targets based on the enhancement of speckle patterns with the hybrid input-output algorithm

Qianqian Cheng, Enlai Guo, Qianying Cui, Jing Han, Lianfa Bai

Author Affiliations +

Proceedings Volume 11761, Fourth International Conference on Photonics and Optical Engineering; 1176119 (2021) https://doi.org/10.1117/12.2586639
Event: Fourth International Conference on Photonics and Optical Engineering, 2020, Xi'an, China

Abstract

Recovering the object hidden in the disorganized speckle pattern generated through diffusive materials is an important topic as well as a difficult challenge. Existing speckle correlation imaging approaches generally use the speckle autocorrelation to extract the Fourier amplitude information of the target. Our goal here is to research the effects of the quality of the speckle autocorrelation on reconstructing targets via HIO-ER (hybrid input-output and the error reduction) algorithm. Specifically, a low-quality speckle pattern is preprocessed to estimate a high-quality autocorrelation. The PSNR of preprocessed autocorrelations could be increased from 5.88 dB to 24.08 dB. We also compare the differences between the preprocessed and unprocessed methods, and the reconstruction quality could be significantly improved than the later one. The result indicates that a high-quality speckle autocorrelation obtained after preprocessing helps to optimize reconstructing targets

Citation Download Citation

Qianqian Cheng, Enlai Guo, Qianying Cui, Jing Han, and Lianfa Bai "Reconstructing targets based on the enhancement of speckle patterns with the hybrid input-output algorithm", Proc. SPIE 11761, Fourth International Conference on Photonics and Optical Engineering, 1176119 (15 January 2021); https://doi.org/10.1117/12.2586639

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