Illumination Pattern Research Articles

Extended-depth of field random illumination microscopy, EDF-RIM, provides super-resolved projective imaging

The ultimate aim of fluorescence microscopy is to achieve high-resolution imaging of increasingly larger biological samples. Extended depth of field presents a potential solution to accelerate imaging of large samples when compression of information along the optical axis is not detrimental to the interpretation of images. We have implemented an extended depth of field (EDF) approach in a random illumination microscope (RIM). RIM uses multiple speckled illuminations and variance data processing to double the resolution. It is particularly adapted to the imaging of thick samples as it does not require the knowledge of illumination patterns. We demonstrate highly-resolved projective images of biological tissues and cells. Compared to a sequential scan of the imaged volume with conventional 2D-RIM, EDF-RIM allows an order of magnitude improvement in speed and light dose reduction, with comparable resolution. As the axial information is lost in an EDF modality, we propose a method to retrieve the sample topography for samples that are organized in cell sheets.

Noise-robust and data-efficient compressed ghost imaging via the preconditioned S-matrix method

The design of the illumination pattern is crucial for improving imaging quality of ghost imaging (GI). The S-matrix is an ideal binary matrix for use in GI with non-visible light and other particles since there are no uniformly configurable beam-shaping modulators in these GI regimes. However, unlike widely researched GI with visible light, there is relatively little research on the sampling rate and noise resistance of compressed GI based on the S-matrix. In this paper, we investigate the performance of compressed GI using the S-matrix as the illumination pattern (SCSGI) and propose a post-processing method called preconditioned S-matrix compressed GI (PSCSGI) to improve the imaging quality and data efficiency of SCSGI. Simulation and experimental results demonstrate that compared with SCSGI, PSCSGI can improve imaging quality in noisy conditions while utilizing only half the amount of data used in SCSGI. Furthermore, better reconstructed results can be obtained even when the sampling rate is as low as 5%. The proposed PSCSGI method is expected to advance the application of binary masks based on the S-matrix in GI.

Encryption-decryption scheme in a single-pixel system based on polarization and Laguerre-Gaussian mode modulation

Optical cryptosystems are crucial for ensuring the security of optical information transmission and storage. The indirect measurement mechanism of single-pixel imaging (SPI) offers a feasible implementation channel for optical cryptosystems. Illumination patterns are encryption keys projected onto the plaintext object, while the intensity collected by the single-pixel detector forms the ciphertext. However, the variations in the object's angular position during SPI measurement generally introduce certain inaccuracies in image reconstruction. And due to SPI's input-output linear mapping relationship, the plaintext is vulnerable to exposure. This proposes an encryption-decryption scheme in a single-pixel system based on polarization and Laguerre-Gaussian (LG) mode modulation. The inherent circular symmetry of LG mode makes the angular position of the object information that can be encrypted, while the intrinsic properties of the object can be represented by polarization. Our system characterizes various polarization parameters of samples serving as reliable plaintext with an error of less than 4.2%, including depolarization, diattenuation, and retardance. For encryption demonstration, LG modes are randomly divided into 5 groups, corresponding to an object at different rotational states. This, combined with 16 polarization modulations, constructs pattern-angle-polarization joint keys, enabling high-security encryption as well as high-fidelity decryption of the mask image, optical axis orientation, and retardance of the test sample. Experimental results demonstrate the effectiveness of our scheme in enhancing the security and information complexity of optical cryptography, offering valuable insights for optical communication and quantum information security.

Medium-adaptive compressive diffuse optical tomography.

The low spatial resolution of diffuse optical tomography (DOT) has motivated the development of high-density DOT systems utilizing spatially-encoded illumination and detection strategies. Data compression methods, through the application of Fourier or Hadamard patterns, have been commonly explored for both illumination and detection but were largely limited to pre-determined patterns regardless of imaging targets. Here, we show that target-optimized detection patterns can yield significantly improved DOT reconstructions in both in silico and experimental tests. Applying reciprocity, we can further iteratively optimize both illumination and detection patterns and show that these simultaneously optimized source/detection patterns outperform predetermined patterns in simulation settings. In addition, we show media-adaptive measurement data compression methods enable wide-field DOT systems to recover highly complex inclusions inside optically-thick media with reduced background artifacts. Furthermore, using truncated optimized patterns shows an improvement of 2-4× in increased speed of data acquisition and reconstruction without significantly losing image quality. The proposed method can be readily extended for additional data dimensions such as spectrum and time.

Single-pixel object classification using ordered illumination patterns

The fixed-ordering illumination patterns lack an effective information interchange with objects. This leads to the light intensity values carrying random feature information, affecting the model's building and recognition capability. Furthermore, this method needs numerous illumination pattern projection counts, which results in low sampling efficiency. Therefore, we propose a new optimized-ordering illumination patterns method. In this paper, we first integrate fixed-ordering illumination patterns with category-representative images to obtain light intensity values that carry category feature information. Subsequently, the mechanisms of intra-category feature importance and inter-category feature differences are introduced to reorder the light intensity values and eliminate index numbers to generate an optimized-ordering index array. Finally, based on this index array, illumination patterns are extracted from the original fixed ordering method to form the new optimized-ordering illumination patterns. Experimental results show that in simulation experiments using the MNIST, Fashion MNIST, TRI, and Multi-category datasets, the optimized ordering method achieved recognition accuracies of 90.00%, 80.00%, 80.00%, and 80.00% with only 30 sampling times. Actual tests with physical objects such as mini numbers and clothing also confirmed these findings. The method offers a new research approach by enhancing recognition accuracy and sampling efficiency in single-pixel object classification.

Observing multi-frequency structured illumination patterns based on an evanescent field in a millimeter-scale polymer slide.

Millimeter-scale slide optical waveguides (OWGs) show the potential to break the barrier of easy-to-use and versatility for total internal reflection (TIR) fluorescence technology. In this paper, multi-frequency structured illumination (SI) patterns resulting from the evanescent field (EF) on the surface of a millimeter-scale polymer slide OWG are observed by measuring the fluorescence intensity distribution of fluorescent dyes deposited on the top of the OWG. The frequency, intensity, and stability of the SI patterns show a strong dependence on the coupling angle of the incident light (changing with the incident position). The distribution of multi-frequency SI patterns in the frequency space is demonstrated for different numerical aperture (NA) imaging systems (NA = 0.3, 0.6, and 0.8), indicating the potential for enhanced resolution for low NA systems with a simple and cheap polymer slide.

Adaptive sampling strategy for Fourier single-pixel imaging

Fourier single-pixel imaging is a technique that utilizes Fourier bases as illumination patterns to capture images. While the use of orthogonal bases enhances the imaging quality compared with other methods of single pixel imaging, the slow imaging speed has hindered its broader application. Acquiring only low-frequency Fourier coefficients enables capturing a significant portion of image information at low sampling ratio, thereby enhancing imaging speed. Nevertheless, truncating frequencies results in a loss of image detail and a decrease in picture quality. To address this challenge, this paper introduces an adaptive sampling strategy for Fourier single-pixel imaging, allowing for customized sampling distributions for each specific object. The sampling distribution is dynamically generated based on the acquired Fourier coefficients during the acquisition process, eliminating the need for prior information. Through extensive simulations and experimental analysis, this approach has demonstrated its ability to capture more complex image details at equivalent sampling ratios.

In vivo optogenetics using a Utah Optrode Array with enhanced light output and spatial selectivity

Objective.Optogenetics allows the manipulation of neural circuitsin vivowith high spatial and temporal precision. However, combining this precision with control over a significant portion of the brain is technologically challenging (especially in larger animal models).Approach.Here, we have developed, optimised, and testedin vivo, the Utah Optrode Array (UOA), an electrically addressable array of optical needles and interstitial sites illuminated by 181μLEDs and used to optogenetically stimulate the brain. The device is specifically designed for non-human primate studies.Main results.Thinning the combinedμLED and needle backplane of the device from 300μm to 230μm improved the efficiency of light delivery to tissue by 80%, allowing lowerμLED drive currents, which improved power management and thermal performance. The spatial selectivity of each site was also improved by integrating an optical interposer to reduce stray light emission. These improvements were achieved using an innovative fabrication method to create an anodically bonded glass/silicon substrate with through-silicon vias etched, forming an optical interposer. Optical modelling was used to demonstrate that the tip structure of the device had a major influence on the illumination pattern. The thermal performance was evaluated through a combination of modelling and experiment, in order to ensure that cortical tissue temperatures did not rise by more than 1 °C. The device was testedin vivoin the visual cortex of macaque expressing ChR2-tdTomato in cortical neurons.Significance.It was shown that the UOA produced the strongest optogenetic response in the region surrounding the needle tips, and that the extent of the optogenetic response matched the predicted illumination profile based on optical modelling-demonstrating the improved spatial selectivity resulting from the optical interposer approach. Furthermore, different needle illumination sites generated different patterns of low-frequency potential activity.

Development and Assessment of Multiple Illumination Color Fourier Ptychographic Microscopy for High Throughput Sample Digitization.

In this study, we proposed a multiplexed color illumination strategy to improve the data acquisition efficiency of Fourier ptychography microscopy (FPM). Instead of sequentially lighting up one single channel LED, our method turns on multiple white light LEDs for each image acquisition via a color camera. Thus, each raw image contains multiplexed spectral information. An FPM prototype was developed, which was equipped with a 4×/0.13 NA objective lens to achieve a spatial resolution equivalent to that of a 20×/0.4 NA objective lens. Both two- and four-LED illumination patterns were designed and applied during the experiments. A USAF 1951 resolution target was first imaged under these illumination conditions, based on which MTF curves were generated to assess the corresponding imaging performance. Next, H&E tissue samples and analyzable metaphase chromosome cells were used to evaluate the clinical utility of our strategy. The results show that the single and multiplexed (two- or four-LED) illumination results achieved comparable imaging performance on all the three channels of the MTF curves. Meanwhile, the reconstructed tissue or cell images successfully retain the definition of cell nuclei and cytoplasm and can better preserve the cell edges as compared to the results from the conventional microscopes. This study initially validates the feasibility of multiplexed color illumination for the future development of high-throughput FPM scanning systems.

High dynamic range structured illumination microscopy based on per-pixel coding

Abstract Structured illumination microscopy (SIM) can achieve optical sectioning with high resolution, and have aroused extensive research interest. In SIM, a set of high-contrast illumination patterns are projected onto the sample to modulate the surface height information, and then, a decoding algorithm is applied to the modulated pattern images for high-quality optical sectioning. Applied to samples with large dynamic range of reflectivity, however, SIM may fail to achieve high quality sectioning for accurate surface reconstruction. Herein, an active digital micromirror device (DMD) based illumination method using per-pixel coded strategy is proposed in SIM to realize high-quality measurement for surface with complex reflection characteristics. In this method, the mapping relationship between DMD and the camera is established pixels by pixels, which enables the illumination intensity on the sample surface can be flexibly modulated by DMD pixel-level modulation corresponding to reflectivity distribution of the surface, and allows the camera pixels always to have reasonable exposure intensity for high precision measurement. More importantly, we put forward an adaptive light intensity control algorithm to improves the signal-to-noise ratio of acquired images without compromising modulation depth of pattern and measurement efficiency. Extensive comparative experiments were conducted and demonstrated that the proposed method can retrieve the surface morphology information of micro-scale complex reflectivity surfaces with high accuracy.

Image authentication method based on Fourier zero-frequency replacement and single-pixel self-calibration imaging by diffractive deep neural network

The diffractive deep neural network is a novel network model that applies the principles of diffraction to neural networks, enabling machine learning tasks to be performed through optical principles. In this paper, a fully optical authentication model is developed using the diffractive deep neural network. The model utilizes terahertz light for propagation and combines it with a self-calibration single-pixel imaging model to construct a comprehensive optical authentication system with faster authentication speed. The proposed system filters the authentication images, establishes an optical connection with the Fourier zero-frequency response of the illumination pattern, and introduces the signal-to-noise ratio as a criterion for batch image authentication. Computer simulations demonstrate the fast speed and strong automation performance of the proposed optical authentication system, suggesting broad prospects for the combined application of diffractive deep neural networks and optical systems.

The PAU survey: photometric calibration of narrow band images

ABSTRACT The physics of the accelerating Universe (PAU) camera is an optical narrow band and broad band imaging instrument mounted at the prime focus of the William Herschel Telescope. We describe the image calibration procedure of the PAU survey data. We rely on an external photometric catalogue to calibrate our narrow band data using stars that have been observed by both data sets. We fit stellar templates to the stellar broad-band photometry of the Sloan Digital Sky Survey and synthesize narrow band photometry that we compare to the PAUS narrow band data to determine their calibration. Consequently, the PAUS data are in the AB system as inherited from its reference calibrator. We do several tests to check the performance of the calibration. We find it self-consistent when comparing repeated observations of the same objects, with a good overall accuracy to the AB system which we estimate to be at the 2 per cent precision level and no significant trends as a function of narrow band filter or wavelength. Repeated observations allow us to build a spatial map of the illumination pattern of the system. We also check the wavelength dependence of the calibration comparing to stellar spectra. We find that using only blue stars reduces the effects of variations in the stellar template fitting to broad-band colours, improving the overall precision of the calibration to around 1 per cent and its wavelength uniformity. The photometric redshift performance obtained with the PAUS data attests to the validity of our calibration to reach the PAUS science goals.

Super-Resolution by Localized Plasmonic Structured Illumination Microscopy Using Self-Assembled Nanoparticle Substrates

Structured illumination microscopy (SIM), an advanced super-resolution methodology, transcends the traditional diffraction limit inherent in optical imaging. This technique utilizes standing-wave illumination generated through the interplay of two obliquely incident light waves. The intrinsic resolution constraint of SIM, traditionally pegged at half the wavelength because of the standing wave’s periodicity, has the potential for enhancement by integrating high spatial frequency illumination patterns, particularly when sourced in the near-field of plasmonic nanostructures. The present study introduces and computationally validates a novel, easily fabricated substrate composed of self-assembled gold nanoparticles designed explicitly for generating these high spatial frequency patterns. Addressing the necessity for diverse patterns in reconstructing super-resolution imagery within plasmonic SIM, this research conducted extensive numerical simulations of nanoparticle arrays under varying illumination scenarios. This undertaking affirmed the feasibility of manipulating high-frequency patterns. Super-resolution reconstruction was actualized by applying Blind-SIM techniques, which verified its effectiveness. This innovative approach notably achieved a resolution threshold of 60 nm, markedly exceeding the conventional 150 nm diffraction barrier and surpassing the 75 nm resolution typically observed in standard SIM applications.

Toward robust super-resolution imaging: A low-rank approximation approach for pattern-illuminated Fourier ptychography

Pattern-illuminated Fourier ptychography (piFP) is an elegant combination of structured illumination imaging and a Fourier ptychographic algorithm with the ability to image beyond the diffraction limit of the employed optics. Artifact-free piFP super-resolution reconstruction requires a high level of stability in the illumination pattern. However, unpredictable pattern variation occurs in the presence of environment perturbation, intensity fluctuation, and pointing instability at the source, leading to declines in image reconstruction quality. To address this issue, we present an efficient and robust piFP algorithm based on low-rank approximation (LRA-piFP), which relaxes the requirement for the stability of illumination patterns. This LRA-piFP method can model frame-wise pattern variation during a full scan, thus improve the reconstruction quality significantly. We take numerical simulations and proof-of-principle experiments with both long-range imaging and microscopy for demonstrations. Results show that the LRA-piFP method can handle different kinds of pattern variation and outperforms other state-of-the-art techniques in terms of reconstruction quality and resolution improvement. Our method provides effective experimental robustness to piFP with a natural algorithmic extension, paving the way for its application in both macroscopic and microscopic imaging.

All-dielectric super-lattice metasurfaces with fivefold spatial resolution enhancement for structured illumination microscopy.

Structured illumination microscopy (SIM) is a promising imaging technique for high-resolution imaging with a wide field of view. Although a periodic nanostructure is a versatile platform for engineering the spatial frequency of structured illumination patterns in SIM, challenges remain, including artifacts from Fourier space gaps. We designed an all-dielectric super-lattice metasurface (ADSLM) to generate structured illumination patterns with enhanced spatial frequency and broadened spatial frequency coverage with no intermediate frequency gaps. Our numerical simulations reveal that ADSLM-based image reconstruction is capable of producing high-contrast, artifact-free images, resulting in enhanced spatial resolution up to 5.7-fold for coherent SIM at 450 nm. Our results show that the ADSLM-SIM technique may facilitate high-resolution imaging using CMOS-compatible substrates, offering potential for compact miniaturized imaging applications.

Single-molecule localization microscopy at 2.4-fold resolution improvement with optical lattice pattern illumination

Traditional camera-based single-molecule localization microscopy (SMLM), with its high imaging resolution and localization throughput, has made significant advancements in biological and chemical researches. However, due to the limitation of the fluorescence signal-to-noise ratio (SNR) of a single molecule, its resolution is difficult to reach to 5 nm. Optical lattice produces a nondiffracting beam pattern that holds the potential to enhance microscope performance through its high contrast and penetration depth. Here, we propose a new method named LatticeFLUX which utilizes the wide-field optical lattice pattern illumination for individual molecule excitation and localization. We calculated the Cramér-Rao lower bound of LatticeFLUX resolution and proved that our method can improve the single molecule localization precision by 2.4 times compared with the traditional SMLM. We propose a scheme using 9-frame localization, which solves the problem of uneven lattice light illumination. Based on the experimental single-molecule fluorescence SNR, we coded the image reconstruction software to further verify the resolution enhancement capability of LatticeFLUX on simulated punctate DNA origami, line pairs, and cytoskeleton. LatticeFLUX confirms the feasibility of using 2D structured light illumination to obtain high single-molecule localization precision under high localization throughput. It paves the way for further implementation of ultra-high resolution full 3D structured-light-illuminated SMLM.

Printing Completely Conformal Liquid Metal Circuits on Arbitrary Curved Surfaces via Customized Conformal Mask

Owing to the excellent mechanical adaptability to curved surfaces and high circuit flexibility, conformal electronics have been developed for extensive applications including aeronautics and wearable electronics. However, conventional methods for fabricating conformal circuits are often constrained by planar structures, limiting the design flexibility and applicability of electronic devices on more complex and varied surfaces. In this study, we propose a facial approach by combining a 3D‐printed customized conformal mask (CCM) with liquid metal inkjet printing, to establish the completely conformal liquid alloy circuits printing technique on arbitrary curved surfaces. We develop a two‐dimensional transient mathematical model to simulate the particle deposition process during inkjet printing and predict the form of the circuits on curved surfaces. Moreover, we characterize parameters such as line resistance and cross‐sectional morphology of liquid metal circuits on both deformable and non‐deformable surfaces. Various conformal liquid metal circuits, such as contour lines, expressions, text patterns, LED array illumination patterns, and multi‐channel pressure array intelligent skin on curved surfaces are demonstrated. Compared to traditional conformal electronics manufacturing methods, this new approach offers the advantages of simple processes, flexibility, low cost (within $0.01/cm2), and high efficiency (exceeding 1cm2/s), making it suitable for mass conformal electronics production.This article is protected by copyright. All rights reserved.

Manipulation of large, irregular-shape particles using contour-tracking optical tweezers.

While the optical tweezers technique is a promising tool for manipulation of microparticles, its application to large (>50 µm) particles and irregular-shape ones is still a hard task. In this Letter, we propose what is to our knowledge a novel concept of contour-tracking optical tweezers (CTOTs), which extract the contour of the objective particle to form the illumination pattern of the trapping laser into the contour shape in real time. We demonstrated the trapping of polystyrene particles of irregular shape with the size of over 100 µm with CTOTs. Our approach has potential to open the way for expanding the applicability of optical tweezers by enabling manipulation of a variety of samples.

Fourier space aberration correction for high resolution refractive index imaging using incoherent light

An aberration correction method is introduced for 3D phase deconvolution microscopy. Our technique capitalizes on multiple illumination patterns to iteratively extract Fourier space aberrations, utilizing the overlapping information inherent in these patterns. By refining the point spread function based on the retrieved aberration data, we significantly improve the precision of refractive index deconvolution. We validate the effectiveness of our method on both synthetic and biological three-dimensional samples, achieving notable enhancements in resolution and measurement accuracy. The method's reliability in aberration retrieval is further confirmed through controlled experiments with intentionally induced spherical aberrations, underscoring its potential for wide-ranging applications in microscopy and biomedicine.

Differentiable design of a double-freeform lens with multi-level radial basis functions for extended source irradiance tailoring

Freeform optics are key for generating prescribed illumination patterns from given sources, which are crucial for solid-state lighting and machine vision illumination. There is an increasing demand for compact freeform optics, which presents a substantial challenge for current design methods since the source dimensions must be considered. Most current extended-source design methods, although requiring profound knowledge of optics and mathematics, focus on the modest goal of obtaining uniform irradiance distributions. We address a more challenging design problem of generating an irradiance distribution of arbitrary shape through a double-freeform lens that can fully encompass the extended source. We propose a differentiable design method whose uniqueness lies in the representation of the double-freeform surfaces using multi-level spherical radial basis functions, which has a natural link to a multi-scale optimization technique. In addition, we employ a sequential unconstrained minimization technology complemented with Lagrange multipliers that add key feasibility constraints on lens shape and size. The proposed method is flexible, general, and efficient in designing highly compact freeform lenses for generating both simple and complex irradiance distributions, as demonstrated through the design examples. This could enable a universal solution to the extended-source design problem.