This work presents an innovative approach to simulating image formation in the human eye by developing a bionic eye model. Commercial software is employed to create an accurate model of the human eye for simulating eye images. Accordingly, A physical bionic human eye model is crafted to explore the imaging properties of eye images and validate the image quality of the eye model, with a liquid lens embedded as the crystalline lens for accommodating the eye at different object distances. To comprehensively assess the performance of the bionic eye model, digital holography is utilized to measure and analyze the wavefronts of the eye model to understand the aberrations of the bionic human eye and their impact on image quality. This study provides a thorough evaluation of the performance of the proposed eye model to enhance the accuracy of bionic eye imaging.
This work presents a disordered metadiffuser that can achieve a uniform angular scattering distribution with a numerical aperture (NA) of 0.85 at a working wavelength of λ=532 nm, as demonstrated through simulations using the Gerchberg- Saxton algorithm. Additionally, we demonstrate the capability of the metadiffuser to achieve near diffraction-limit high NA focusing (NA>0.8) through the use of a spatial light modulator and the optical phase conjugation method for wavefront shaping. Finally, we propose a deep ultraviolet (DUV) model-based optical proximity correction (OPC) system that uses optical and photoresist simulations via Hopkins’s partially coherent image formation and fully convolutional networks (FCN). This system enables larger-area device fabrication with DUV lithography while maintaining precise critical dimension (CD) of meta atoms. The proposed OPC system achieves a lithography accuracy with an average ΔCD/CD of 0.235%. These results offer promising implications for the practical application of metadiffusers and the DUV lithography technique in the field of optical devices.
The work describes deep learning-enabled holographic tomography for neuroblastoma cell processing, analysis, and diagnosis through three-dimensional (3-D) cell Refractive Index (RI) model. Deep learning-assisted approach is applied to execute effective segmentation of 3-D RI cell morphology for the different cellular states under normal, autophagy, and apoptosis. The biophysical parameters of 3-D RI cell morphology are analyzed and selected for learning-based classification to identify cell death pathways. The results show that the proposed approach achieve of 98% in identifying cell morphology through optimized biophysical parameters.
This work further develops a recently proposed time-resolved inline digital holography (TRIDH) [Petrov, N. V. et al. Opt. Lett. 43, 3481 (2018)] for studying degenerate phase modulation induced by an inclined collimated pump beam in the glass substrate with the quantum dots at the surface. Similar to many techniques for measuring nonlinear properties of materials, it is based on a comparison of the prediction obtained by the mathematical model of the phenomenon with experimental data. We have extended the mathematical model for the case of interaction of two femtosecond laser pulses in the double-layered sample. The impact of the ratio between nonlinear refractive indexes of two layers and their thicknesses on induced phase modulation is analyzed.
We introduce a novel phase-only diffractive optical element called chiral binary square axicon (CBSA). The CBSA is designed by linearly rotating the square half-period zones of the binary square axicon with respect to one another. A quadratic phase mask (QPM) is combined with the CBSA using modulo-2π phase addition technique to bring the far-field intensity pattern of CBSA at the focal plane of the QPM and to introduce quasiachromatic effects. The periodically rotated zones of CBSA produce a whirlpool phase profile and twisted intensity patterns at the focal plane of QPM. The degree of twisting seen in the intensity patterns is dependent upon the angular step size of rotation of the zones. The intensity pattern was found to rotate around the optical axis along the direction of propagation. The phase patterns of CBSA with different angles of zone rotation are displayed on a phase-only spatial light modulator, and the experimental results were found to match with the simulation results. To evaluate the optical trapping capabilities of CBSA, an optical trapping experiment was carried out and the optical fields generated by CBSA were used for trapping and rotating yeast cells.
KEYWORDS: Defect detection, Digital holography, Diffraction, Image classification, 3D image reconstruction, Optical inspection, Glasses, Digital watermarking, Digital imaging, Defect inspection
High demand of optical inspection is increased to guarantee manufacture and product quality in industries. To overcome limitations of the manual defect inspection, machine vision inspection is needed to efficiently and accurately screen the undesired defects on various products. Recently, the transparent substrate is becoming widely used for manufacturing optics and electronics products. For high-grade transparent substrates, development of machine vision inspection has increased its importance for inspecting defects after production. To perform machine vision inspection for the transparent substrate, the exposure procedure and analysis of the capturing image are critical challenges due to its properties of reflection and transparency. However, conventional machine vision systems are performed for optical inspection based on two-dimensional (2D) intensity images from the camera-based photography without phase and depth information, and may decrease inspection accuracy as well as defect classification. Conversely, instead of the 2D intensity image by camera-based photography with complicated algorithms and time-consuming computation, digital holography is a novel three-dimensional (3D) imaging technique to rapidly access the whole wavefront information of the target sample for optical inspection and complex defect analysis. In this study, we propose digital holographic imaging of transparent target sample for optical inspection in learning-based pattern classification, which a novel complex defect inspection model is presented for multiple defects identification of the transparent substrate based on 3D diffraction characteristics and machine learning algorithm. Both theoretical and experimental results will be presented and analyzed to verify the effective inspection and high accuracy.
KEYWORDS: 3D modeling, Digital holography, Calibration, Tomography, 3D image processing, Reconstruction algorithms, Holography, Microscopy, 3D image reconstruction, Holograms
In previous study, a tomographic imaging system is built up for measuring the three-dimensional refractive index distribution inside the micrometer-sized biological cell by optically driven full-angle rotation scheme based on digital holographic microscopy, named as optical-driven tomographic DHM (OT-DHM) system. However, a small perturbation of the system will lead the inaccurate of the positions and the orientation of the micrometer-sized sample, thus the automatic calibration of the reconstructed phase images in the OT-DHM system is required. For this purpose, a novel model-based algorithm is proposed, in which we employ a 3-D ellipse shape for modeling the samples. The parameters of the ellipse-like shape on a small number of the projections are estimated and used them to build up the 3-D ellipse model of the samples. In advance, the reconstructed phase images are highly contaminated by the uneven background and coherence speckle noise. The block-based between-class criterion is used to suppress the effect of the non-uniform background, and the anisotropic diffusion process is utilized for the noise cleaning, including shot noise and speckles noise on the reconstructed phase. The boundary of the cell in each projection can be considered as the 2-D ellipse, and used to estimate the parameters of the 2-D ellipse. The established 3-D ellipse shape is applied for the calibration of the spatial positions and the orientations of the all other rotational angles. With the automatic calibration algorithm, the OT-DHM system can effectively reconstructed the three-dimensional refractive index distribution inside the micrometer-sized samples.
A setup using fringe projection techniques to perform 3D profile measurements for transparent objects is presented. The related mathematical equations are derived as well. A fringe pattern is illuminated onto the transparent object. Fringes passing through the inspected object are then projected onto a screen. A CCD camera is employed to record the transmitted fringes on the screen. Fringe on the screen are deformed by the refractive index and the surface structure, and therefore are desirable to describe the shape of the inspected sample.
This work describes the image formation and properties of holographic three-dimensional (3-D) display based on spatial light modulators (SLMs) combined with optical imaging systems. Existing pixelated SLMs with periodic mesh structures affect the holographic reconstruction and display properties. According to a holographic 3-D display architecture based on SLM in paraxial optical systems, this study applied the ray matrix optics and scalar diffraction theory to regard the light wave emitting from the holographic plane to the image plane as an optical system composed of four matrix elements. The image quality and depth of field (DOF) of the holographic 3-D display system are investigated, and the relationship between the impulse response and the matrix elements of the holographic imaging system is derived. In addition, the imaging properties and DOF are explored and verified through optical experimentation.
An approach using the fringe projection technique to perform the 3D profile measurement for a plano-convex lens is
proposed. A fringe pattern is illuminated onto the lens object, and a CCD camera is employed to record the transmitted
fringes on the screen. Fringes on the obtained image are deformed both by the refractive index and the topography of the
object, and are analyzable to retrieve the 3D shape.
We investigate the practical design of a complex-encoded key mask for optical encryption and decryption based on joint transform correlation architecture. The mask is created by using two coupled liquid-crystal spatial light modulators, one operating in amplitude mode and the other in phase mode. We develop a modified iterative Fourier transformation algorithm to design an optimal complex key mask, which is applied and mapped to the complex modulation of the liquid-crystal devices for optical implementation. The limitations of the devices on the system design are investigated and analyzed. The width constraints of the key mask are also derived, based on the joint transform correlation architecture for optical realization. Experimental results show the decryption performance and the shift-invariance of the complex key mask.
To achieve the full complex modulated range of the cascaded twisted nematic liquid crystal spatial light modulator (TNLC-SLM), we propose and demonstrate a novel amplitude compensated technique. Optical reconstructions of complex digital holograms with higher image quality are discussed in both analytical and experimental results.
This work presents an experimental demonstration of an optical joint transform correlator based on the wavelet subband filter for texture pattern recognition. The optical wavelet subband filter is implemented using 4f filtering architecture and utilized to extract the texture features of fingerprints under noisy environments through frequency- and orientation-selective properties. The filtered texture features with noise reduction are applied to optimize recognition via joint transform correlation. Experimental results show that the optical wavelet subband filter enhances the significant texture features from corrupted fingerprints and increases the pattern discrimination of the joint transform correlator.
We propose and demonstrate an optical watermarking scheme using a digital holographic technique. The holographic watermark is constructed by an off-axis diffuse-type hologram and embedded into a cover image with appropriate weighting. Detection of the hidden mark is optically implemented using a VanderLugt correlator with the watermarked matched filter. Detected correlation is spatially separable and avoids interference from the cover image.
We consider the possibility of restoration and/or enhancement of decaying holograms in photorefractive media by using a simple optical readout in conjunction with a phase conjugator. The results indicate that extremely weak holograms can be enhanced provided that the two-beam coupling is sufficiently strong. Steady-state photorefractive holograms can be maintained continuously without decay by using a properly designed readout scheme. The result also provides an explanation for the formation of mutually pumped phase conjugation in terms of the amplification of initial noise gratings.
An optical learning network using photorefractive holograms with grating amplitude detection is presented and demonstrated. The Stoke's principle for light is used to realize both bipolar weight changes and bipolar activities for perceptron learning. The bipolar detection is achieved by using a double Mach-Zehnder interferometer and an electronic subtractor at the output port. Experimental results show that a zero or near to zero threshold value, the network can be trained to dichotomize the input patterns.
A learning-based image recognition system using a thin photorefractive crystal plate is presented and demonstrated. The matched filter is synthesized by the modified perceptron learning network and is recorded in a 100 micrometers thick LiNbO3 crystal plate. The system performs a shift-invariant correlation for image recognition.
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