Open AccessComputational superoscillation imaging beyond the Rayleigh limit from far-Field measurements
Author(s) -
Lianlin Li,
Fang Li,
Tie Jun Cui
Publication year - 2014
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.22.005431
Subject(s) - optics , microwave imaging , regularization (linguistics) , limit (mathematics) , computer science , physics , rayleigh scattering , image resolution , medical imaging , inverse problem , algorithm , microwave , artificial intelligence , mathematics , telecommunications , mathematical analysis
Far-field imaging beyond the Rayleigh limit is one of the most important challenges in optics, microwave, and ultrasonics. We propose a novel sparsity-promoted super-oscillation imaging scheme for reconstructing more universal objects in subwavelength scales, which solves a weighted optimization problem constrained by lp-norm-based sparsity regularization (0≤p≤1). We demonstrate numerically that the proposed imaging technique improves the resolution related to existing approaches remarkably for the case of very high signal-to-noise ratio (SNR), including the traditional super-oscillation imaging and sparsity-based super-resolution imaging. The standard superoscillation based super-resolution imaging approach can be regarded as the first-iteration solution of the proposed scheme. Numerical results for one- and two-dimensional super-resolution imaging are presented for validation.