Efficient sparse Fourier single-pixel imaging

Rong Yan; Daoyu Li; Liheng Bian

doi:10.1117/12.2643470

4 January 2023 Efficient sparse Fourier single-pixel imaging

Rong Yan, Daoyu Li, Liheng Bian

Proceedings Volume 12317, Optoelectronic Imaging and Multimedia Technology IX; 1231704 (2023) https://doi.org/10.1117/12.2643470
Event: SPIE/COS Photonics Asia, 2022, Online Only

Abstract

Fourier single-pixel imaging (FSI) acquisition time is tied to the number of modulations. FSI has a tradeoff between efficiency and accuracy. This work reports a mathematical analytic tool for efficient sparse FSI sampling. It is an efficient and adjustable sampling strategy to capture more information about scenes with reduced modulation times. Specifically, we first conduct the statistical importance ranking of Fourier coefficients of natural images. We design a sparse sampling strategy for FSI with a polynomially decent probability of the ranking. The sparsity of the captured Fourier spectrum can be adjusted by altering the polynomial order. We utilize a compressive sensing (CS) algorithm for sparse FSI reconstruction. From quantitative results, we have obtained the experiential rules of optimal sparsity for FSI under different noise levels and at different sampling ratios.

Conference Presentation

Citation Download Citation

Rong Yan, Daoyu Li, and Liheng Bian "Efficient sparse Fourier single-pixel imaging", Proc. SPIE 12317, Optoelectronic Imaging and Multimedia Technology IX, 1231704 (4 January 2023); https://doi.org/10.1117/12.2643470

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