title: Computational superoscillation imaging beyond the Rayleigh limit from far-field measurements.
abstract: 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.
authors.forename: Lianlin
authors.initials: L
authors.lastname: Li
authors.forename: Fang
authors.initials: F
authors.lastname: Li
authors.forename: Tie Jun
authors.initials: TJ
authors.lastname: Cui