Extreme ultraviolet lensless imaging without object support through rotational diversity in diffractive shearing interferometry

Beurs, A.C.C. de; Liu, Xiaomeng; Jansen, G. S. Matthijs; Konijnenberg, A. P.; Coene, W.; Eikema, K.S.E.; Witte, Stefan

doi:10.1364/oe.380056

Cited by 5 publications

(4 citation statements)

References 26 publications

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“…For typical physical values in a real experiment, we refer to Refs. [12][13][14]. The initial guess for the algorithm is chosen to be an object transmission function equal to one for all pixels (one is also the maximum value of the object).…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Initially, it was proposed to solve this DSI phase retrieval problem using a support constraint [12]. Later, it was proposed to eliminate the need for a support constraint by generating diversity in the constraints M j (k) by rotating the shearing vector dk j , in a method termed rotational DSI (R-DSI) [13,14]. It has been investigated experimentally how varying the interference pattern with which the sample is illuminated can be used in phase retrieval [15].…”

Section: Introductionmentioning

confidence: 99%

“…[16], constraints of the form of Eq. ( 2) are considered for multiple shears dk j , just as in R-DSI [13,14]. In Ref.…”

Section: Introductionmentioning

confidence: 99%

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Phase retrieval algorithms for lensless imaging using diffractive shearing interferometry

et al. 2020

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Diffractive shearing interferometry (DSI) is a method that has recently been developed to perform lensless imaging using extreme ultraviolet radiation generated by high-harmonic generation. In this paper, we investigate the uniqueness of the DSI solution and the requirements for the support constraint size. We find that there can be multiple solutions to the DSI problem that consist of displaced copies of the actual object. These alternative solutions can be eliminated by enforcing a sufficiently tight support constraint, or by introducing additional synthetic constraints. We furthermore propose a new DSI algorithm inspired by the analogy with coherent diffractive imaging (CDI) algorithms: the original DSI algorithm is in a way analogous to the hybrid input–output algorithm as used in CDI, and we propose a new algorithm that is more analogous to the error reduction algorithm as used in CDI. We find that the newly proposed algorithm is suitable for final refinement of the reconstruction.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Phase retrieval algorithms for lensless imaging using diffractive shearing interferometry

et al. 2020

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“…In most approaches, the key to solve the phase problem is to capture the propagated object wavefront on several decorrelated diffraction patterns (e.g., 11 ). The decorrelation can be generated by lateral shearing 12 , using tilt diffraction model 13 , displacing the sensor plane along the optical axis 14 , or ptychography [15][16][17] . Another possibility is to extend the system with more illumination wavelengths.…”

Section: Introductionmentioning

confidence: 99%

SSR-PR: Single-shot Super-Resolution Phase Retrieval based two prior calibration tests

Kocsis,

Shevkunov,

Katkovnik

et al. 2021

Preprint

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We propose a novel approach and algorithm based on two preliminary tests of the optical system elements to enhance the super-resolved complex-valued imaging. The approach is developed for inverse phase imaging in a single-shot lensless optical setup. Imaging is based on wavefront modulation by a single binary phase mask. The preliminary tests compensate errors in the optical system and correct a carrying wavefront, reducing the gap between real-life experiments and computational modeling, which improve imaging significantly both qualitatively and quantitatively. These two tests are performed for observation of the laser beam and phase mask along, and might be considered as a preliminary system calibration. The corrected carrying wavefront is embedded into the proposed iterative Single-shot Super-Resolution Phase Retrieval (SSR-PR) algorithm. Improved initial diffraction pattern upsampling, and a combination of sparse and deep learning based filters achieves the super-resolved reconstructions. Simulations and physical experiments demonstrate the high-quality super-resolution phase imaging. In the simulations, we showed that the SSR-PR algorithm corrects the errors of the proposed optical system and reconstructs phase details 4× smaller than the sensor pixel size. In physical experiment 2 µm thick lines of USAF phase-target were resolved, which is almost 2× smaller than the sensor pixel size and corresponds to the smallest resolvable group of used test target. For phase bio-imaging, we provide Buccal Epithelial Cells reconstructed in computational super-resolution and the quality was of the same level as a digital holographic system with 40× magnification objective. Furthermore, the single-shot advantage provides the possibility to record dynamic scenes, where the framerate is limited only by the used camera. We provide an amplitude-phase video clip of a moving alive single-celled eukaryote.

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Ultra-broadband diffractive imaging with unknown probe spectrum

Chen,

Gu,

Liu

2024

Light Sci Appl

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Strict requirement of a coherent spectrum in coherent diffractive imaging (CDI) architectures poses a significant obstacle to achieving efficient photon utilization across the full spectrum. To date, nearly all broadband computational imaging experiments have relied on accurate spectroscopic measurements, as broad spectra are incompatible with conventional CDI systems. This paper presents an advanced approach to broaden the scope of CDI to ultra-broadband illumination with unknown probe spectrum, effectively addresses the key challenges encountered by existing state-of-the-art broadband diffractive imaging frameworks. This advancement eliminates the necessity for prior knowledge of probe spectrum and relaxes constraints on non-dispersive samples, resulting in a significant extension in spectral bandwidth, achieving a nearly fourfold improvement in bandlimit compared to the existing benchmark. Our method not only monochromatizes a broadband diffraction pattern from unknown illumination spectrum, but also determines the compressive sampled profile of spectrum of the diffracted radiation. This superiority is experimentally validated using both CDI and ptychography techniques on an ultra-broadband supercontinuum with relative bandwidth exceeding 40%, revealing a significantly enhanced coherence and improved reconstruction with high fidelity under ultra-broadband illumination.

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Extreme ultraviolet lensless imaging without object support through rotational diversity in diffractive shearing interferometry

Cited by 5 publications

References 26 publications

Phase retrieval algorithms for lensless imaging using diffractive shearing interferometry

Phase retrieval algorithms for lensless imaging using diffractive shearing interferometry

SSR-PR: Single-shot Super-Resolution Phase Retrieval based two prior calibration tests

Ultra-broadband diffractive imaging with unknown probe spectrum

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