Open AccessSingle exposure lensless subpixel phase imaging: optical system design, modelling, and experimental study
Author(s) -
Péter Kocsis,
Igor Shevkunov,
Vladimir Katkovnik,
Карен Егиазарян
Publication year - 2020
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.379785
Subject(s) - subpixel rendering , phase retrieval , wavefront , optics , computer science , nyquist–shannon sampling theorem , phase modulation , coherent diffraction imaging , image resolution , algorithm , optical transfer function , robustness (evolution) , interferometry , computer vision , phase noise , physics , pixel , fourier transform , biochemistry , chemistry , quantum mechanics , gene
Design and optimization of lensless phase-retrieval optical system with phase modulation of free-space propagation wavefront is proposed for subpixel imaging to achieve super-resolution reconstruction. Contrary to the traditional super-resolution phase-retrieval, the method in this paper requires a single observation only and uses the advanced Super-Resolution Sparse Phase Amplitude Retrieval (SR-SPAR) iterative technique which contains optimized sparsity based filters and multi-scale filters. The successful object imaging relies on modulation of the object wavefront with a random phase-mask, which generates coded diffracted intensity pattern, allowing us to extract subpixel information. The system's noise-robustness was investigated and verified. The super-resolution phase-imaging is demonstrated by simulations and physical experiments. The simulations included high quality reconstructions with super-resolution factor of 5, and acceptable at factor up to 9. By physical experiments 3 μm details were resolved, which are 2.3 times smaller than the resolution following from the Nyquist-Shannon sampling theorem.