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Multifocal microscopes (MFMs) are becoming increasingly popular in fluorescence microscopy due to their high speed three-dimensional (3D) imaging capabilities. Conventional MFMs use a fixed fabricated grating as the multifocal grating but these are limited to a restricted wavelength range and a fixed object-plane separation. Spatial light modulators (SLMs) represent an alternative to fabricated gratings due to their real-time programmability, providing complete control over emission wavelength range and object plane separations. However, algorithms commonly used to obtain multifocal grating patterns which provide uniform intensity across the subimages are not directly applicable to SLM-based MFMs due to inherent pixel-to-pixel crosstalk effects present in the SLM chip. We recently developed an in-situ iterative algorithm which generates grating patterns that provide near-uniform illumination of the subimages in SLM-based MFMs. This algorithm is universal across wavelengths, object-plane separations, and SLM manufacturers. As part of our efforts to develop an SLM-based MFM that can respond rapidly to changing experimental parameters, we implement a gradient descent-based optimization method. We evaluate its performance in comparison with a grid search based routine. Experimental results obtained on a custom-made SLM-based MFM indicate that the grid-search optimized grating patterns provide superior subimage intensity uniformity versus the gradient-descent method. These experiments also provide an insight into the energy landscape involved in these optimizations. This study increases the utility of SLM-based MFMs in high-speed imaging.

Biological processes such as processive enzyme turnover and intracellular cargo trafficking involve the dynamic motion of a small ”article" along a curvilinear biopolymer track. To understand these processes that occur across multiple length and time scales, one must acquire both the trajectory of the particle and the position of the track along which it moves, possibly by combining high-resolution single-particle tracking with conventional microscopy. Yet, usually there is a significant resolution mismatch between these modalities: while the tracked particle is localized with a precision of 10 nm, the image of the surroundings is limited by optical diffraction, with 200 nm lateral and 500 nm axial resolutions. Compared to the particle's trajectory, the surrounding curvilinear structure appears as a blurred and noisy image. This disparity in the spatial resolutions of the particle trajectory and the surrounding curvilinear structure image makes data reconstruction, as well as interpretation, particularly challenging. Analysis is further complicated when the curvilinear structures are oriented arbitrarily in 3D space. Here, we present a prior-apprised unsupervised learning (PAUL) approach to extract information from 3D images where the underlying features resemble a curved line such as a filament or microtubule. This three-stage framework starts with a Hessian-based feature enhancement, which is followed by feature registration, where local line segments are detected on repetitively sampled subimage tiles. In the final stage, statistical learning, segments are clustered based on their geometric relationships. Principal curves are then approximated from each segment group via statistical tools including principal component analysis, bootstrap and kernel transformation. This procedure is characterized on simulated images, where sub-voxel medium deviations from true curves have been achieved. The 3D PAUL approach has also been implemented for successful line localization in experimental 3D images of gold nanowires obtained using a multifocal microscope. This work not only bridges the resolution gap between two microscopy modalities, but also allows us to conduct 3D super line-localization imaging experiments, without using super-resolution techniques.

Presented for the first time is a machine learning enhanced optical distance sensor. The distance sensor is based on our previously demonstrated distance measurement technique that uses an Electronically Controlled Variable Focus Lens (ECVFL) with a laser source to illuminate a target plane with a controlled optical beam spot. This spot with varying spot sizes is viewed by an off-axis camera and the spot size data is processed to compute the distance. In particular, proposed and demonstrated in this paper is the use of a regularized polynomial regression based supervised machine learning algorithm to enhance the accuracy of the operational sensor. The algorithm uses the acquired features and corresponding labels that are the actual target distance values to train a machine learning model. The optimized training model is trained over a 1000 mm (or 1 m) experimental target distance range. Using the machine learning algorithm produces a training set and testing set distance measurement errors of

A microscopy platform that leverages the arrival time of individual photons to enable 3D single-particle tracking of fast-moving (translational diffusion coefficient of ≃3.3 µm2/s) particles in high-background environments is reported here. It combines a hardware-based time-gating module, which enables the rate of photon processing to be as high as 100 MHz, with a two-photon-excited 3D single-particle tracking confocal microscope to enable high sample penetration depth. Proof-of-principle experiments where single quantum dots are tracked in solutions containing dye-stained cellulose, are shown with tracking performance markedly improved using the hardware-based time-gating module. Such a microscope design is anticipated to be of use to a variety of communities who wish to track single particles in cellular environments, which commonly have high fluorescence and scattering background.

Multifocal microscopy affords fast acquisition of microscopic 3D images. This is made possible using a multifocal grating optic; however, this induces chromatic dispersion effects in the point spread function, impacting image quality and single-molecule localization precision. To minimize this effect, researchers use narrow-band emission filters. However, the choice of optimal emission filter bandwidth in such systems is, thus far, unclear. This work presents a theoretical framework to investigate how the localization precision of a point emitter is affected by the emission filter bandwidth. We calculate the Cramér–Rao lower bound for the 3D position of a single emitter imaged using a chromatic multifocal microscope. Simulation results for a range of emission bandwidth systems show that in the absence of background photons and detector noise localization improves for broader emission filter bandwidth due to increased photon throughput despite a larger chromatic dispersion. When realistic background and measurement noise sources are considered in the imaging process being simulated, there is an optimal bandwidth (not the broadest emission filter bandwidth) which provides the highest localization precision. This study provides a framework for optimally designing chromatic multifocal optics and serves as a theoretical foundation for interpretting results.

Proposed is a single viewing axis optical Three-Dimensional (3-D) shape sensor using an electronically controlled variable focus lens (ECVFL) for non-contact smallest transverse resolution reconstructions at all axial direction target planes. The demonstrated completely automated sensor design also involves input beam aperture control for balancing aberration and diffraction effects, enabling minimum focused sampling beam diameter. Sensor design analysis is presented, including the derivation of the depth of field of the camera used in the 3-D sensor. A computer-controlled sensor system using a liquid ECVFL is built and experimentally calibrated for a 40-mm-depth scan with a better than $52~\mu \text{m}$ transverse resolution over a $400~\textrm {mm} \times 400$ mm mechanically implemented transverse scan zone. The 3-D sensor system is successfully deployed to measure the borehole depths in a 3-D sample containing 12 boreholes, image the pin regions of a 16-pin Integrated Circuit (IC) Thin-Shrink Small Outline Package (TSSOP), and reconstruct the shape of a 3-D aircraft part. The sensor gave a ±3% average measurement error for the borehole test sample compared with a vernier caliper measurement. The proposed single viewing axis sensor is ideal for applications requiring cavity or borehole inspections as well as parts requiring high transverse resolution imaging.

Presented is an active no moving parts Depth From Defocus (DFD) system for autofocus and three-dimensional (3-D) imaging applications. The proposed system uses highly coherent laser light and its beam conditioning optics to realize an active illumination system suited for long range and large field of view imaging, overcoming the limited field of view in previous active DFD systems. This is the first time an active DFD system is implemented and experimentally demonstrated using an Electronically Controlled Variable Focus Lens (ECVFL) as an imaging lens that electrically varies the focal length to acquire images with different degrees of defocus, necessary for DFD operations. An experimental demonstration of the proposed system acting as a distance sensor is compared to an incoherent illumination projector DFD system tested over a 1 m range. Apart from showing the effectiveness of the ECVFL as an imaging optic for cameras implementing DFD based autofocus algorithms, presented experimental results for the novel system indicate a depth measurement percentage error of

Proposed is a novel eye vision testing system based on micromachines that uses micro-optic, micromechanic, and microelectronic technologies. The micromachines include a programmable micro-optic lens and aperture control devices, pico-projectors, Radio Frequency (RF), optical wireless communication and control links, and energy harvesting and storage devices with remote wireless energy transfer capabilities. The portable lightweight system can measure eye refractive powers, optimize light conditions for the eye under testing, conduct color-blindness tests, and implement eye strain relief and eye muscle exercises via time sequenced imaging. A basic eye vision test system is built in the laboratory for near-sighted (myopic) vision spherical lens refractive error correction. Refractive error corrections from zero up to −5.0 Diopters and −2.0 Diopters are experimentally demonstrated using the Electronic-Lens (E-Lens) and aperture control methods, respectively. The proposed portable eye vision test system is suited for children’s eye tests and developing world eye centers where technical expertise may be limited. Design of a novel low-cost human vision corrective eyewear is also presented based on the proposed aperture control concept. Given its simplistic and economical design, significant impact can be created for humans with vision problems in the under-developed world.

This paper describes a motionless active Depth from Defocus (DFD) system design suited for long working range camera autofocus applications. The design consists of an active illumination module that projects a scene illuminating coherent conditioned optical radiation pattern which maintains its sharpness over multiple axial distances allowing an increased DFD working distance range. The imager module of the system responsible for the actual DFD operation deploys an electronically controlled variable focus lens (ECVFL) as a smart optic to enable a motionless imager design capable of effective DFD operation. An experimental demonstration is conducted in the laboratory which compares the effectiveness of the coherent conditioned radiation module versus a conventional incoherent active light source, and demonstrates the applicability of the presented motionless DFD imager design. The fast response and no-moving-parts features of the DFD imager design are especially suited for camera scenarios where mechanical motion of lenses to achieve autofocus action is challenging, for example, in the tiny camera housings in smartphones and tablets. Applications for the proposed system include autofocus in modern day digital cameras.

Since 1997, we have proposed and demonstrated the use of the Texas Instrument (TI) Digital Micromirror Device (DMD) for various non-display applications including optical switching and imaging. In 2009, we proposed the use of the DMD to realize wavefront splitting interferometers as well as a variety of imagers. Specifically, proposed were agile electronically programmable wavefront splitting interferometer designs using a Spatial Light Modulator (SLM) such as (a) a transmissive SLM, (b) a DMD SLM and (c) a Beamsplitter with a DMD SLM. The SLMs operates with on/off or digital state pixels, much like a black and white state optical window to control passage/reflection of incident light. SLM pixel locations can be spatially and temporally modulated to create custom wavefronts for near-common path optical interference at the optical detectors such as a CCD/CMOS sensor, a Focal Plane Array (FPA) sensor or a point-photodetector. This paper describes the proposed DMD-based wavefront splitting interferometer and imager designs and their relevant experimental results.

Proposed and experimentally demonstrated is the CAOS-CMOS camera design that combines the coded access optical sensor (CAOS) imager platform with the CMOS multi-pixel optical sensor. The unique CAOS-CMOS camera engages the classic CMOS sensor light staring mode with the time-frequency-space agile pixel CAOS imager mode within one programmable optical unit to realize a high dynamic range imager for extreme light contrast conditions. The experimentally demonstrated CAOS-CMOS camera is built using a digital micromirror device, a silicon point-photo-detector with a variable gain amplifier, and a silicon CMOS sensor with a maximum rated 51.3 dB dynamic range. White light imaging of three different brightness simultaneously viewed targets, that is not possible by the CMOS sensor, is achieved by the CAOS-CMOS camera demonstrating an 82.06 dB dynamic range. Applications for the camera include industrial machine vision, welding, laser analysis, automotive, night vision, surveillance and multispectral military systems. (C) 2016 Optical Society of America

To the best of the authors’ knowledge, proposed is the first embedded optics and electronics-based agile pixel broadband optical imager and spectrum analyzer using a single digital micromirror device (DMD) for laser beam hotspot detection. Specifically, the novel design engages both the wavelength-dependent grating structure of the DMD optical chip and its three-tilt-state micromirror programmability to form both an optical spectrum analyzer (OSA) and an agile pixel imager within one basic instrument. Also, to our knowledge, presented for the first time for a DMD chip is a complete mathematical analysis for incident laser beam operations via diffraction theory. Using off-the-shelf components and the Texas Instruments (TI) Lightcrafter DLP chip and drive electronics, embedded engineering of the proposed instrument is implemented for the visible laser wavelength band. Experimental OSA operation of the instrument is demonstrated using classic laser wavelengths of 633 and 532 nm with beam power levels of 20 and 180 mW, respectively. Experimental imaging operation of the instrument compared with a commercial scanning slit-based laser beam profiler is successfully conducted for a 633 nm test laser beam having a hotspot with ∼68% peak-to-null power drop near its center. Applications for the proposed imager-OSA instrument include laser beam testing during laser assembly and manufacturing operations.