Image Aberrations Research Articles

Numerical Study of Customized Artificial Cornea Shape by Hydrogel Biomaterials on Imaging and Wavefront Aberration

The blindness caused by cornea diseases has exacerbated many patients all over the world. The disadvantages of using donor corneas may cause challenges to recovering eye sight. Developing artificial corneas with biocompatibility may provide another option to recover blindness. The techniques of making individual artificial corneas that fit the biometric parameters for each person can be used to help these patients effectively. In this study, artificial corneas with different shapes (spherical, aspherical, and biconic shapes) are designed and they could be made by two different hydrogel polymers that form an interpenetrating polymer network for their excellent mechanical strength. Two designed cases for the artificial corneas are considered in the simulations: to optimize the artificial cornea for patients who still wear glasses and to assume that the patient does not wear glasses after transplanting with the optimized artificial cornea. The results show that the artificial corneas can efficiently decrease the imaging blur. Increasing asphericity of the current designed artificial corneas can be helpful for the imaging corrections. The differences in the optical performance of the optimized artificial corneas by using different materials are small. It is found that the optimized artificial cornea can reduce the high order aberrations for the second case.

Post hoc Correction of Chromatic Aberrations in Large-Scale Volumetric Images in Confocal Microscopy.

Over the last decade, tissue-clearing techniques have expanded the scale of volumetric fluorescence imaging of the brain, allowing for the comprehensive analysis of neuronal circuits at a millimeter scale. Multicolor imaging is particularly powerful for circuit tracing with fluorescence microscopy. However, multicolor imaging of large samples often suffers from chromatic aberration, where different excitation wavelengths of light have different focal points. In this study, we evaluated chromatic aberrations for representative objective lenses and a clearing agent with confocal microscopy and found that axial aberration is particularly problematic. Moreover, the axial chromatic aberrations were often depth-dependent. Therefore, we developed a program that is able to align depths for different fluorescence channels based on reference samples with fluorescent beads or data from guide stars within biological samples. We showed that this correction program can successfully correct chromatic aberrations found in confocal images of multicolor-labeled brain tissues. Our simple post hoc correction strategy is useful to obtain large-scale multicolor images of cleared tissues with minimal chromatic aberrations.

Digital optofluidic compound eyes with natural structures and zooming capability for large-area fluorescence sensing

Compound eyes are ubiquitous natural biosensors that possess high temporal resolution and large fields of view (FOVs). While for solid materials based artificial imaging systems, flexible zooming ability while keeping the constant FOV is still challenging, as well as the low-cost fabrication. Herein, liquid compound eyes with natural structures are presented that synthesize optofluidics and bionics in a non-trivial manner, which enables the deformation-free zooming and flexible cell fluorescence sensing. Experimental results indicate that the innovatively manufactured bionic template possesses low roughness and uniform lens configuration with more than two thousands units, which endows the eyes with high-quality and low aberration imaging ability. Besides, digital controlled miscible liquids switching enables the focus of ommatidia simultaneously be adjusted from 150 μm to 5 mm with 100° view angle, and without bending the microlens curvature, to avoid FOV changing and image aberration. Due to large FOV and tunable ability, large-area cell fluorescence signal arrays and dynamic cell motion are imaged using this liquid compound eyes. This work presents novel strategy for compound lens manufacture at low-cost, and proposes deformation-free and continuous focus-tuning strategy, offering potentials for numerous applications, including biomedical sensing and adaptive imaging with large FOV.

Design of a high-resolution holographic waveguide eye-tracking system operating in near-infrared with conventional optical elements.

The eye-tracking system plays an essential role in the augmented reality (AR) eyewear. Waveguide volume holographic optical elements (HOE) that can be made with high efficiency, thin form, and lightweight are well-suited for this application. Traditional holographic lenses formed with spherical wavefronts at visible wavelengths and used for near-infrared (NIR) eye-tracking systems suffer from significant image aberrations, image tilt, and ghost images. This work describes a complete holographic lens design methodology that systematically addresses these issues and details the specifications of conventional optical elements that provide the optimized wavefronts for the hologram construction beams. The resulting waveguide HOE NIR eye-tracking system has an image resolution of ∼10 lp/mm when the designed holographic lens is deposited on a waveguide with a refractive index of 1.8 and thickness of 0.5 mm.

Imaging from the visible to the longwave infrared wavelengths via an inverse-designed flat lens.

It is generally assumed that correcting chromatic aberrations in imaging requires multiple optical elements. Here, we show that by allowing the phase in the image plane to be a free parameter, it is possible to correct chromatic variation of focal length over an extremely large bandwidth, from the visible (Vis) to the longwave infrared (LWIR) wavelengths using a single diffractive surface, i.e., a flat lens. Specifically, we designed, fabricated and characterized a flat, multi-level diffractive lens (MDL) with a thickness of ≤ 10µm, diameter of ∼1mm, and focal length of 18mm, which was constant over the operating bandwidth of λ=0.45µm (blue) to 15µm (LWIR). We experimentally characterized the point-spread functions, aberrations and imaging performance of cameras comprised of this MDL and appropriate image sensors for λ=0.45μm to 11μm. We further show using simulations that such extreme achromatic MDLs can be achieved even at high numerical apertures (NA=0.81). By drastically increasing the operating bandwidth and eliminating several refractive lenses, our approach enables thinner, lighter and simpler imaging systems.

Tunable fluidic lens with a dynamic high-order aberration control.

Fluidic lenses based on electrowetting actuation are attractive for their wide focal tuning range, yet are limited by optical aberrations, either intrinsic to the lenses themselves or due to the optical imaging systems in which they are employed. However, the ability to control the meniscus shape that forms the lens refractive surface with a high degree of spatial accuracy will allow correction of and compensation for a wide range of these aberrations. We demonstrate here for what we believe, to the best of our knowledge, is the first time a tunable optofluidic lens controlled by 32 azimuthally placed electrodes for which most aberrations up to the fourth radial Zernike order may be corrected. Using both wavefront sensing and sensorless wavefront estimation techniques, it is shown that focal length tunability with a significant reduction in imaging aberrations and the ability to compensate for externally induced aberrations may be achieved using a single component.

Metalenses: from design principles to functional applications.

Lens is a basic optical element that is widely used in daily life, such as in cameras, glasses, and microscopes. Conventional lenses are designed based on the classical refractive optics, which results in inevitable imaging aberrations, such as chromatic aberration, spherical aberration and coma. To solve these problems, conventional imaging systems impose multiple curved lenses with different thicknesses and materials to eliminate these aberrations. As a unique photonic technology, metasurfaces can accurately manipulate the wavefront of light to produce fascinating and peculiar optical phenomena, which has stimulated researchers' extensive interests in the field of planar optics. Starting from the introduction of phase modulation methods, this review summarizes the design principles and characteristics of metalenses. Although the imaging quality of existing metalenses is not necessarily better than that of conventional lenses, the multi-dimensional and multi-degree-of-freedom control of metasurfaces provides metalenses with novel functions that are extremely challenging or impossible to achieve with conventional lenses.

Aberrations in ultrasound images are not just noise

Researchers present an ultrasound imaging technique to reveal aberrating structures in a sample that would otherwise be invisible.

A Color Restoration Algorithm for Diffractive Optical Images of Membrane Camera.

In order to verify the technology of the membrane diffractive imaging system for Chinese next generation geo-stationary earth orbit (GEO) satellite, a series of ground experiments have been carried out using a membrane optical camera with 80 mm aperture (Φ80) lens. The inherent chromatic aberration due to diffractive imaging appears in the obtained data. To address the issue, an effective color restoration algorithm framework by matching, tailoring, and non-linearly stretching the image histograms is proposed in this letter. Experimental results show the proposed approach has good performances in color restoration of the diffractive optical images than previous methods. The effectiveness and robustness of the algorithm are also quantitatively assessed using various color deviation indexes. The results indicate that the chromatic aberration of diffractive images can be effectively removed by about 85%. Also, the proposed method presents reasonable computational efficiency.

Machine vision based online detection of PCB defect

The traditional PCB defect on-line detection has the problems of long detection time and poor accuracy of detection results. Therefore, a key technology of PCB defect online detection based on machine vision is proposed. Firstly, image retrieval is carried out by using visual detection algorithm, image smoothing, image contrast enhancement, image sharpening and other preprocessing operations are carried out by using gray-scale transformation algorithm to simplify the operation process and improve the image quality; secondly, PC is analyzed B. the causes and types of defects. The original color image is processed and binarized by the hybrid recognition method of mathematical morphology and pattern recognition. Then the reference image obtained by mathematical morphology method is used as a template for system self inspection. Finally, the image aberration detection algorithm is introduced to segment the threshold value of PCB defect image, remove redundant points and mark PCB image defect recognition results, improve the visual detection algorithm and optimize the hardware design to achieve PCB image defect detection and recognition. The experimental results show that the method has high detection accuracy and short detection time, and can effectively control the stable operation of the online detection system, which provides a reference for related research in this field.

Aberration-corrected three-dimensional positioning with a single-shot metalens array

Three-dimensional (3D) positioning with the correction of imaging aberrations in the photonic platform remains challenging. Here, we combine techniques from nanophotonics and machine vision to significantly improve the imaging and positioning performance. We use a titanium dioxide metalens array operating in the visible region to realize multipole imaging and introduce a cross-correlation-based gradient descent algorithm to analyze the intensity distribution in the image plane. This corrects the monochromatic aberrations to improve the imaging quality. Analysis of the two-dimensional aberration-corrected information in the image plane enables the 3D coordinates of the object to be determined with a measured relative accuracy of 0.60%–1.31%. We also demonstrate the effectiveness of the metalens array for arbitrary incident polarization states. Our approach is single-shot, compact, aberration-corrected, polarization-insensitive, and paves the way for future integrated photonic robotic vision systems and intelligent sensing platforms that are feasible on the submillimeter scale, such as face recognition, autonomous vehicles, microrobots, and wearable intelligent devices.

Calibration-free quantitative phase imaging using data-driven aberration modeling.

We present a data-driven approach to compensate for optical aberrations in calibration-free quantitative phase imaging (QPI). Unlike existing methods that require additional measurements or a background region to correct aberrations, we exploit deep learning techniques to model the physics of aberration in an imaging system. We demonstrate the generation of a single-shot aberration-corrected field image by using a U-net-based deep neural network that learns a translation between an optical field with aberrations and an aberration-corrected field. The high fidelity and stability of our method is demonstrated on 2D and 3D QPI measurements of various confluent eukaryotic cells and microbeads, benchmarking against the conventional method using background subtractions.

Two-dimensional multifibre spectral image correction based on machine learning techniques

ABSTRACT Owing to the limited size and imperfections of the optical components in a spectrometer, aberrations inevitably make their way into 2D multifibre spectral images in the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST), which leads to obvious spatial variation of the point spread functions (PSFs). However, if spatially variant PSFs are estimated directly, the large storage and intensive computational requirements result in the deconvolution spectrum extraction method becoming intractable. In this paper, we propose a novel method to solve the problem of spatial variation of the PSFs through image aberration correction. When CCD image aberrations are corrected, the convolution kernel can be approximated by only one spatially invariant PSF. Specifically, a novel method based on machine learning is proposed to calibrate the distorted spectral images. The method includes many techniques, such as total least squares (TLS) algorithm, self-supervised learning and multilayer feed-forward neural networksnetworks, and it makes use of a special training set sampling scheme combining 2D distortion features in a flat-field spectrum and calibration lamp spectrum. The calibration experiments on the LAMOST CCD images show that the proposed method is feasible. Furthermore, the spectrum extraction results before and after calibration are compared, and the experimental results show that the characteristics of the extracted 1D waveform are closer to those of an ideal optics system after image correction, and that the PSF of the corrected object spectrum estimated by the blind deconvolution method is nearly centrosymmetric, which indicates that our proposed method can significantly reduce the complexity of spectrum extraction and improve extraction accuracy.

Inverse-designed achromatic flat lens enabling imaging across the visible and near-infrared with diameter > 3 mm and NA = 0.3

It is generally thought that correcting chromatic aberrations in imaging requires multiple surfaces. Here, we show that by allowing the phase in the image plane of a flat lens to be a free parameter, it is possible to correct chromatic aberrations over a large continuous bandwidth with a single diffractive surface. In contrast to conventional lens design, we utilize inverse design, where the phase in the focal plane is treated as a free parameter. This approach attains a phase-only (lossless) pupil function, which can be implemented as a multi-level diffractive flat lens that achieves achromatic focusing and imaging. In particular, we experimentally demonstrate imaging using a single flat lens of diameter > 3 mm and focal length = 5 mm (NA = 0.3, f/1.59) that is achromatic from λ = 450 nm (blue) to 1 μm (NIR). This simultaneous achievement of large size, NA, and broad operating bandwidth has not been demonstrated in a flat lens before. We experimentally characterized the point-spread functions, off-axis aberrations, and broadband imaging performance of the lens.

Effects of rare earth elements on the microstructure and wear properties of TiB2 reinforced aluminum matrix composite coatings: Experiments and first principles calculations

In this work, effects of rare earth elements on microstructure evolution and wear properties of TiB2 reinforced aluminum matrix composite coatings were investigated by the combination of first principles calculations and experimental investigation. The calculated results revealed that Sc exhibited the most effective modification ability due to the most negative adsorption energy and the largest charge transfer compared with La and Y. Based on the calculated results, the rare earth elements modified composite coatings were synthesized by laser processing. The as-obtained composites were characterized by back-scattered electron imaging (BSE) and spherical aberration corrected scanning transmission electron microscopy (Cs-corrected STEM). Results indicated that the addition of Sc can greatly refine the particle size of TiB2, improve the distribution of particles and lead to the morphology transforming from hexagonal disk to sphere. As a result, the microhardness and wear properties of the composite coatings were enhanced significantly. The best properties were achieved in the composite with 0.6 wt% Sc addition, which exhibited highest microhardness of 920 HV, lowest friction coefficient of 0.4 and wear rate of 24.8 mg /h. The preferential adsorption of rare earth elements on TiB2 facets is proposed to be the main modification mechanism which results in the morphology evolution and wear properties improvement.

Multi-scale sensorless adaptive optics: application to stimulated emission depletion microscopy.

Sensorless adaptive optics is commonly used to compensate specimen-induced aberrations in high-resolution fluorescence microscopy, but requires a bespoke approach to detect aberrations in different microscopy techniques, which hinders its widespread adoption. To overcome this limitation, we propose using wavelet analysis to quantify the loss of resolution due to the aberrations in microscope images. By examining the variations of the wavelet coefficients at different scales, we are able to establish a multi-valued image quality metric that can be successfully deployed in different microscopy techniques. To corroborate our arguments, we provide experimental verification of our method by performing aberration correction experiments in both confocal and STED microscopy using three different specimens.

Complete and accurate data correction for seamless mosaicking of airborne hyperspectral images: A case study at a mining site in Inner Mongolia, China

Airborne hyperspectral remote sensing is an important application in the ecological monitoring of the environment in mining areas, and accurate preprocessing of the original images is the key to quantitative information retrieval. The original image data need radiation correction to acquire surface reflectance data. Due to the impact of the field angle, incidental radiance, and the bidirectional reflectance distribution function (BRDF), there can be a brightness gradient between adjacent strips, which leads to radiance difference and obvious chromatic aberration of the mosaicked images. We propose a novel data correction method for seamless mosaicking of airborne hyperspectral images. Firstly, visible and near-infrared (VNIR) and shortwave infrared (SWIR) sensors are calibrated in the laboratory, and the radiation calibration model of the sensor is established by an integrating-sphere system. A correction function is then established by combining the BRDF effect and the radiation attenuation coefficients. We also normalize the exposure time, sun altitude angle, and sensor altitude angle according to the flight strip. The results showed that this method is able to eliminate the signal distortion, allowing the seamless mosaicking of 37 strip images which were taken in different date and conditions in the study area. After the atmospheric correction of the imagery was completed, the accuracy of the preprocessing results was evaluated by field-measured ASD spectroradiometer data. The coefficient of determination R2 of the results for the reflectance was greater than 0.9. The experiments show that the proposed method has a good performance in radiation accuracy, and can provide high-quality hyperspectral data for the follow-up application of the ecological monitoring of a mining area.

Image distortion, pupil coma, and relative illumination.

Relative illumination is affected by image distortion, pupil coma, and pupil magnification. Image and pupil aberrations have a known relationship that also can be written in terms of pupil magnification. Pupil coma is the stretching or compression of the pupil along the field axis, which directly affects relative illumination. Front-stopped designs have pupil aberrations on the exit pupil while rear-stopped systems have pupil aberrations on the entrance pupil. Of the primary pupil aberrations, pupil coma can have the largest effect on the relative illumination in optical designs with significant image distortion (ex: fisheye lens). The Lagrange invariant holds for systems with image distortion using a paraxial approximation of pupil coma. Relative illumination can be written in terms of % distortion, pupil magnification, and object-space field angle.

A polynomial-division based correction model for camera calibration: a large comparative study

These days, algorithms which enable correction of an image aberration such us barrel or pillow distortion can be found in a large number of scientific papers. Some sorts of algorithms have universal character, others can be used only with a certain type of optical systems. This paper compares several types of methods which were designed to remove an image distortion. The methods which are based on so called Polynomial Division Model (PDM) are only considered. On the grounds of extensive experimental results, a method which uses the polynomial division model was proposed. The method brought significantly better results in the correction process. It does not matter if the images are loaded with a pillow or a barrel distortion. The image correction calculation procedure is from a general point of view, very time demanding. The calculation with use of the PDM is fast, and does not need a large number of members of the correction polynomial. This rule is also valid for an image which is loaded with large distortion e.g., for Fish-Eye object-lenses - a newly proposed PDM preserves all good features of previous algorithms which are based on the PDM and extends them. All the results which are recorded in the experimental section show that the PDM is superior and more effective in comparison to other tested methods.

General defocusing particle tracking: fundamentals and uncertainty assessment

General Defocusing Particle Tracking (GDPT) is a single-camera, three-dimensional particle tracking method that determines the particle depth positions from the defocusing patterns of the corresponding particle images. GDPT relies on a reference set of experimental particle images which is used to predict the depth position of measured particle images of similar shape. While several implementations of the method are possible, its accuracy is ultimately limited by some intrinsic properties of the acquired data, such as the signal-to-noise ratio, the particle concentration, as well as the characteristics of the defocusing patterns. GDPT has been applied in different fields by different research groups, however, a deeper description and analysis of the method fundamentals has hitherto not been available. In this work, we first identity the fundamental elements that characterize a GDPT measurement. Afterwards, we present a standardized framework based on synthetic images to assess the performance of GDPT implementations in terms of measurement uncertainty and relative number of measured particles. Finally, we provide guidelines to assess the uncertainty of experimental GDPT measurements, where true values are not accessible and additional image aberrations can lead to bias errors. The data were processed using DefocusTracker, an open-source GDPT software. The datasets were created using the synthetic image generator MicroSIG and have been shared in a freely-accessible repository.