This study investigates the use of a recently published generalized scaling law [J. Opt. Soc. Am. A 33(12), 2477-2484 (2016)]. In practice, the generalized scaling law accurately predicts the diffraction-limited peak irradiance in the far-field given the beam power, wavelength, propagation distance, field-effective area, and field-out-coupling factor. After reviewing this scaling-law formulation, we compare the far-zone predictions for peak irradiance and Gaussian beam spread to wave-optics simulations. Overall, the results show that this scaling-law formulation does not predict the correct peak irradiance, nor the correct Gaussian beam spread for horizontal-path scenarios with varying levels of atmospheric turbulence.

A full description of light propagation in the ray regime is provided by the plenoptic function, where both the location and angle of each ray is known. In this paper, we investigate the utility of plenoptic data for extracting information from a scene where the light from objects in the scene is viewable only after scattering from a diffuse surface. The detected light is mathematically described as a light field that varies as a function of both space and propagation angle. The relationship between the object light field and the scattered light field is cast in terms of a system of Fredholm integral equations of the first kind, where the bidirectional reflectance distribution function (BRDF) of the scattering surface is incorporated into the kernel of the integral equations. The object information from the original scene is retrieved by solving the resulting system of integral equations.

We apply our mathematics to BRDFs containing the superposition of a quasi shift-invariant specular component and a diffuse component. This permits the use of efficient Fourier methods to solve the integral equations. These analytical solutions are verified via numerical simulation. In addition, we show experimental results from a light-field measurement studio equipped with a high-dynamic range scientific camera connected to a high-precision motorized stage. This studio is capable of measuring light fields with high accuracy. Experimental results of reconstructed light-fields will be reported.

Formation of images in strong turbulence (spherical-wave log-amplitude variance greater than 0.25) is a well-known challenge. Such imaging with coherent active illumination poses special difficulties due to the presence of laser speckle in the image, which is similar to atmospheric speckle and so it is difficult to separate the two forms of speckle. However, imaging with laser illumination has the potential benefit of enhanced signal and added information in the laser speckle. In this paper, several image processing approaches are investigated with simulation that show promise for good image quality in such conditions. These approaches include pupil-plane techniques that filter phase based on an assumed atmospheric spatial phase structure function, branch-cut filtering and intensity-weighted branch cut minimization. Also included in the analyses are focal-plane techniques. Significant improvements can be found for Rytov variances up to and beyond 0.4 and up to 10 atmospheric coherence lengths (r₀) across the aperture, in uniform turbulence scenarios over a 30 km range with objects of limited extent. The approaches are optimized for fast execution and minimal number of image frames required to form an acceptable image. The results are compared using several image metrics and also compared with a corresponding idealized adaptive-optics approach using an incoherent beacon.

A continuous-face-sheet Xinetics deformable mirror (DM) is characterized and analyzed using Fizeau interferometer measurements. The influence of each individual actuator on the DM surface is measured. The measured data is then processed to be used as influence functions that define the influence of each actuator on the DM surface. Using the measured data as a spanning set, an orthonormal basis is computed for the span of the set using singular value decomposition. Real surface measurements are taken of the orthonormal basis influences to test for both linear independence of the actuators and actuator linearity with respect to voltage. The efficacy of using the measured basis function data to converge toward a more accurate basis in an iterative process is evaluated. Performance of lower rank (compressed) bases are also evaluated.

This study uses traditional wave-optics techniques, such as the split-step beam propagation method with angular-spectrum propagation, to explore the number of branch points as a function of the numerical grid size (i.e., the branch-point density) with increasing strengths of turbulence. To help quantify the strength of the turbulence, the analysis makes use of the log-amplitude variance for a spherical wave. Given a point-source beacon and horizontal-propagation paths, this parameter gives a straightforward gauge for the amount of scintillation, and therefore the number of branch points in the phase function. As such, the goal throughout is to investigate the branch-point density in terms of a two-step process. The first step is to increase the numerical grid size to have an ever increasing number of grid points for a given instance of turbulence; particularly, with a log-amplitude variance for a spherical wave above 0.25, because this is where branch points start to arise in the phase function. In turn, the second step is to utilize a Monte-Carlo averaging scheme with the resultant branch-point density for many instances of turbulence and turbulence strengths. Using this two-step process, the initial results show that the branch-point density grows without bound. Such results seem unphysical and could have direct implications for wave-optics studies that involve wavefront sensing in the presence of deep turbulence.

In this study we use a series of computational-wave-optics experiments to look at the statistics associated with speckle fields resulting from a tilted flat plate (i.e. one that is optically rough compared to the wavelength of plane-wave illumination). To help quantify the strength of the simulated speckle, we make use of the target Fresnel number. This parameter gives a gauge for the number of speckles across the receiver. The goal throughout is to show that, frame to frame, the analysis can appropriately simulate correlated speckle fields in terms of the magnitude of the complex degree of coherence as a function of tilt. The results show that the simulated speckle fields are properly correlated from frame to frame, and this outcome leads to the ability to perform closed-loop-phase-compensation studies in the presence of extended beacons. Such studies are becoming increasingly important for applications that involve imaging through turbulence.

This study uses the split-step beam propagation method (BPM) to look at the Monte Carlo statistics associated with increasing strengths of turbulence and steady state thermal blooming (SSTB). To help quantify the strength of the turbulence and SSTB, the analysis makes use of two parameters: the analytical log-amplitude variance and the distortion number. These parameters simplify greatly given horizontal-propagation paths with constant index-of-refraction structure coefficients and extinction coefficients. As such, the goal throughout is to characterize the impact of turbulence thermal blooming interaction (TTBI) in terms of multiple metrics of interest. These metrics include the spatial-structure function, magnitude of the complex degree of coherence, and log-amplitude variance. The results show that the presence of thermal blooming causes the log- amplitude variance to increase significantly from the theoretical value. This outcome leads to an interesting trade-space analysis with respect to TTBI.

The Air Force Research Laboratory Directed Energy Directorate is building a supersonic wind tunnel in order to characterize aero-optical effects. In order to gain access to the test section of interest, we must first send light through the access windows of the wind tunnel’s test section. Thus, one of the initial challenges we face is being able to characterize the aberrations caused by the boundary-layer effects over the look-through windows separate from the aberrations caused by aero-optical effects over the test section of interest. As such, we are designing a dual wave-front sensor (WFS) setup in order to characterize these phenomena. The completed product will use a Shack-Hartmann (SH) WFS, in addition to a digital holography (DH) WFS. For all intents and purposes, the data obtained from the SH WFS will serve as the baseline for all experimentation, since it is the tried and true method for wavefront sensing in a wind tunnel environment. The DH WFS, on the other hand, is a unique method for wavefront sensing in a wind-tunnel environment. By providing us with access to an estimate of the complex-optical field, the DH WFS has the potential to transcend the capabilities of the SH WFS. In particular, we should be able to numerically propagate to various planes of interest in the optical train to characterize boundary layer effects over the look-through windows, separate from the aero-optical effects over the test section of interest. This paper reviews the requirements of our wind-tunnel environment and the design for this proposed dual WFS setup.

A modal wavefront sensor is known for its quick detection, flexibility and simplicity in the measurement of the various aberration modes (in the form of an orthogonal basis set such as the Zernike modes) present in the wavefront of an incident beam. But the output of these type of sensor suffers from inter-modal crosstalk that may arise due to the coexistence of a large number of aberration modes in the incident beam. This leads to degradation of the quality of the sensor output, resulting in inaccuracy in the measurement of aberration modes. Booth et al. provided an optimized expression of the sensor output that reduced the inter-modal cross-talk and improved the linear response of the sensor to a great extent. However, the issue of cross-talk still persists and the sensor for a particular mode is still vulnerable to the presence of other modes. In the present work, we present an analytical study of the influence of inter-modal cross-talk on the output of a holographic modal wavefront sensor for various aberration modes. Theoretical, simulation and experimental results are presented for better visualization of the cross-talk effect.

In the new generation of giant telescopes with high resolution images, the atmospheric turbulence has become an obstacle to the precision of the results. The use of adaptive optics is now crucial for wavefront correction in such telescopes.

The most commonly used sensor in adaptive optics is the Shack-Hartmann Wavefront Sensor. Composed of an array of lenses, it uses a reference, normally a star, to sample the wavefront tilts in the primary aperture. By processing the tilts at each sub-aperture, it is possible to estimate the overall disturbance.

Since adaptive optics systems require high luminous intensity, it is common to use artificial guide stars. These stars are generated by a laser focused on the sodium layer in the upper atmosphere. Due to the optical geometry, the laser guide star generates an elongated spot when imaged by a sub-aperture. In giant telescopes larger than 20 meters in diameter, the spot elongation is so large that classical centroiding techniques provide poor results, especially in the presence of spot truncation at the edge of the sub-aperture. Such peculiarities, in addition to the temporal variation of the atmospheric sodium profile, make it difficult to determine the displacement of the image reference and, consequently, to determine the wavefront disturbance.

In this work, we propose a method capable of determining the centroid of the elongated spots even in the presence of truncation. The key ideas are to model the observed images with Poisson noise and to employ a Grid Search strategy to determine the position of the spot. Finally, we show that the proposed method provides better results when compared to current methods.

The Hartmann Turbulence Sensor (HTS) is an optical system capable of estimating several atmospheric turbulence parameters, such as Greenwood frequency, Fried’s coherence diameter and inner scale of turbulence. It primarily comprises of a 40 cm Meade telescope, a 32 x 32 Shack- Hartmann lenslet array, and a high-speed camera. The HTS estimates the turbulence parameters by measuring the local tilts of the aberrated wavefront coming from a laser source and incident at the pupil plane of the telescope. At the Air Force Institute of Technology (AFIT), a technique has been developed to measure the distribution of turbulence along an experimental path using the HTS and two laser sources of the same wavelength. By measuring the variances of the difference in wavefront tilts due to the two sources sensed by a pair of Hartmann subapertures with varying separations, turbulence information along the path can be extracted. The method relies on deriving a set of weighting functions, each weighting function dipping to zero at a range where the two sensing paths from the beacons to the subapertures intersect, thus canceling out the effect of turbulence at this location on the differential tilt signal. The analytical expression for the path weighting functions has been derived here. The technique has been applied to experimental data collected over a 500 m grassy path and the profiling results have been compared to a co-located scintillometer. This work will eventually aid in obtaining a better understanding of turbulence in the lower atmosphere and how it varies with height.

Cross-talk between different modes has always been an intrinsic issue of a modal wavefront sensor. Efforts have been put to reduce the effect of these inter-modal cross-talk either by varying the detector aperture or by changing the mode of intensity measurement at the detector. Since the modal wavefront sensor considers the incident wavefront as a linear combination of some orthogonal basis set, say the Zernike polynomials, the presence of cross-talk between the different modes of these basis set greatly affects the sensor output. As a result the measure of the modal content of the various orthogonal modes in the incident wavefront are affected, leading to inaccuracy in measurements. In this work we present a new method of measurement of the orthogonal modes present in an incident wavefront. The proposed method can be considered as a modified version of the modal wavefront sensing technique proposed by Neil et al, having advantages in terms of cross-talk reduction between modes and linearity enhancement, in the process of measurement of various orthogonal modes present in the incident wavefront. In this paper we also present some of our simulation results in support of our proposed sensing technique.

Deconvolution techniques for removing the effects of diffraction from the Hubble space telescope have been employed for decades. This paper introduces a new solution for the deconvolution problem that separates the measurements into three sets of complete data. These data sets are a function of the unknown neighborhood around a star, the amplitude of the star that is known to exist and the background light and dark current measured during the acquisition process. In this paper the new method is tested with simulated Hubble space telescope data and compared to the traditional RichardsonLucy deconvolution algorithm. The results show that the new method can obtain imaging resolution well beyond the classical diffraction-limit and outperforms the Richardson-Lucy method by a substantial margin.

Recent advances are presented for multiframe blind deconvolution (MFBD) of ground based telescope imagery for low-earth orbit objects. The iterative algorithm uses the maximum likelihood estimation optimization criterion. It is modeled from a previous well-known algorithm called the expectation-maximization (EM) algorithm. New renditions of the algorithm simplify the phase reconstruction, thereby reducing the complexity of the original EM algorithm. Examples are shown, with and without adaptive optics (AO). The system is being designed for on-the-fly streaming video operation.

Several superresolution phenomena are re-visited in the context of the ”prior discrete Fourier transform” (PDFT). The PDFT is used to establish relationships between superresolution imaging applications, the construction of superoscillating signals and the design of superresolution filters. The condition number of the PDFT algorithm is identified as a pivotal parameter for practical applications of the PDFT to superresolution problems. Motivated by applications of the algorithm to imaging from Fourier data, a simple regularization procedure is suggested, which results in superoscillating signals representative of the constraints used for their construction. In addition, bandwidth extrapolation from oversampled data is investigated, which highlights inherent limits of superresolution signal recovery and synthesis.

We discuss the use of nematic liquid-crystal phase modulators (LCPMs) as repeatable, programmable optical disturbance test sources to simulate propagation through deep atmospheric turbulence in a laboratory setting. LCPMs can introduce controlled dynamic aberrations into optical systems at low cost, low complexity and high flexibility. Because they are small they can easily be inserted into the optical path of optics system. The programmed sequence can be modified to simulate changing atmospheric conditions and engagement scenarios. In this paper we describe phase screens generated with multiple LPCMs set up at different conjugate points in an optical path to simulate multiple atmospheric turbulence layers. The goal is to simulate deep turbulence optical propagations to test subsequent wave-front sensors and control algorithms. We investigate phenomena related to deep turbulence propagation such as phase-front branch points and optical field intensity fluctuations with medium to high Rytov number.

The incorporation of polarization control on the illumination beam in a laser scanning confocal microscope allows extraction of the orientational information of submicroscopic features of a sample being studied. In this paper, we present the implementation of an optical arrangement that generates homogeneous as well as non-homogeneous user define polarization profiles over the cross-sectional area of a laser beam. A confocal system is built with this optical arrangement to obtain images of the same target with different polarized illumination beams such that there is considerable reduction in the time gap between two consecutive illuminations of each location of the sample.

We are designing a telescope imaging system based on an apodized diffractive optical element called an apodized photon sieve (APS) in order to detect exoplanets. APSs are orders of magnitude less massive, lightweight and more compactable than mirrors. Proposed imaging system can be installed on any telescope as an "attachment" or used as a telescope itself as a part of a CubeSat payload. Methods were developed for designing the apodized sieves, measuring PSFs, and characterizing high-contrast performance of the imaging system. This new kind of APS has rotational symmetry and provides high-contrast (up to 10^-10 levels) in all directions with just one image with the throughput of 40% or higher.

Turbulence mitigation has long been a challenge in long-distance imaging systems. Holographic aperture ladar (HAL), a multiwavelength spatio-temporal heterodyne 3D imaging modality, is also vulnerable to the deleterious effects of volumetric turbulence along the path of propagation. In this work, we develop a sharpness-maximization turbulence mitigation algorithm using a single phase plane approximation to volumetric turbulence. We show preliminary results that simulated HAL fields aberrated by a single turbulent phase screen, coincident with the pupil, are well corrected using this sharpness-maximization algorithm for turbulence profiles with D/r₀ values of up to 50.

X-ray micro-computed tomography (micro-CT) achieves a spatial resolution of micron or submicron and is well-applied in many fields such as biomedicine, materials and electronic packaging. However, it suffers from low contrast and weak material distinguishability because of its low power of the X-ray source comparing with industrial or medical X-ray source. Recently, we adapt a state-of-the-art photon-counting detector (PCD) in a micro-CT system, leading a spectral Micro-CT. By dividing the X-ray photons into different energy bins, the PCD well maintains the energy-dependent property of matter attenuation and then contributes to selective-reconstruction. The selective-reconstruction problems of spectral micro-CT are ill-posed, i.e., the solution is very sensitive to noise. Meanwhile, for each PCD energy channel, the corresponding photon number is only a small fraction of the emitted photons, which further increases the noise level. To overcome the ill-posedness, in this work, we propose a multi-domain constraint based optimization model for one-step selective-reconstruction. First, we measure the data fidelity in photon domain using the Kullback-Leibler distance (Idivergence) and derive an equivalent expression in channel projection domain. Then, we introduce multi-domain constraints to establish the relationship among channel projections, material projections, and material images. After that, we employ the Mumford-Shah (MS) functional to describe the prior knowledge in the material image domain, such as gradient sparsity and edge information. Finally, we develop an iterative algorithm and verify it with numerical simulations.

After the implantation of metal prostheses, such as hip and knee replacements, there is a need to monitor the success of the implantation and, in some cases, to determine the cause of continuing pain. MRI would be well suited to visualizing the possible changes in soft tissue surrounding the implant, however its success is badly affected by artifacts due to the presence of the metal in the scanner's strong magnetic field. The Dixon method allows the variation in the magnetic field to be estimated, but only as the wrapped phase of a complex quantity. High field gradients near the metal mean that the phase estimate is highly undersampled and challenging to unwrap. In 2017, we reported a new algorithm named POP (phase estimation by onion peeling) and conjectured that our initial implementation for 2-D imaging could be extended to 3-D imaging. This would require expanding the phase estimate using a suitable smoothly varying basis over closed enveloping surfaces which are irregular. The algorithm initially estimates the phase over a surface which surrounds the implant and is sufficiently distant from the implant that the phase is well sampled. Then, surface-by-surface, the smooth nature of the true phase is invoked to form an initial estimate of the true phase on the next surface. That estimate is corrected using the sampled wrapped phase data arising from the MR scan. In this paper, I investigate the choice of basis functions and methods for projecting them onto irregular surfaces which are typical for applying POP to imaging the soft tissue surrounding hip implants.

Image reconstruction models that deal with Poisson noise have received notable attention for image denoising and deblurring problems. Tomography does not fall into this category, and such methods have yet to be explored for applications such as electron tomography, where the noise is dominated by Poisson noise. In this domain, the use of Poisson models becomes much more challenging, where popular methods such as the Richardson-Lucy algorithm cannot be implemented. The purpose of this article is to provide a survey of Poisson image reconstruction models in the context of tomography, and identify the most successful algorithms and the benefits over the current standard techniques. Methods using both ℓ₁ and ℓ₂ regularization techniques are investigated, while the data fitting methods include both iteratively reweighted norms and negatively log-likelihood methods derived from the Bayesian formulation. The results of this work indicate a consistent improvement when implementing the appropriate Poisson models.

High resolution imaging of biological macromolecules using x-ray crystallography is a key component of modern molecular biology, the results of which are essential for understanding biological processes in health and disease, and for drug design. Macromolecular imaging is currently undergoing a revolution as a result of the recent availability of x-ray free-electron lasers (XFELs). XFELs produce extremely intense, ultra-short x-ray pulses which offer the possibility of imaging specimens that are different to the 3D crystals used in conventional x-ray crystallography. The application of XFEL imaging to nano-crystalline fibrous specimens - long, slender systems that are periodic in their axial direction exhibit partial lateral crystallinity - is investigated. It is shown that individual Fourier amplitudes can be measured from XFEL data from such specimens. It is demonstrated that the image reconstruction problem from diffraction data for specimens with reduced crystallinity, specifically 2D membranes, is achievable. Although such specimens are weakly diffracting, they potentially offer more information in their diffraction than do 3D crystals. Image reconstruction is demonstrated by simulation.

Mobile-phone based microscopy often uses 3D-printed opto-mechanical designs and inexpensive optical components that are not optimized for microscopic imaging of specimen. For example, the illumination source is often a battery-powered LED, which can create spectral distortions in the acquired image. Mechanical misalignments of the optical components and the sample holder as well as inexpensive lenses lead to spatial distortions at the microscale. Furthermore, mobile-phones are equipped with CMOS image sensors with a pixel size of ~1-2 µm, which results in an inferior signal-to-noise ratio compared to benchtop microscopes, which are typically equipped with much larger pixels, e.g., ~5-10 µm. Here, we demonstrate a supervised learning framework, based on a deep convolutional neural network for substantial enhancement of a smartphone microscope image, by eliminating spectral aberrations, increasing the signal-to-noise ratio and improving the spatial resolution of the acquired images. Once trained, the deep neural network is fixed, and it rapidly outputs an image, matching the quality of a benchtop microscope image, in a feed-forward, non-iterative manner, without the need for any modeling of the aberrations in the mobile imaging system. This framework is demonstrated using pathology slides of thin tissues sections and blood smears, validating its superior performance even using highly-compressed images, suitable especially for telemedicine applications with restricted bandwidth and storage requirements. This deep learning-powered approach can be broadly applicable to various mobile microscopy systems that can be used for point-of-care medicine and global health related applications.

Adaptive-optics (AO) systems correct the distortions caused by atmospheric turbulence for imaging and laser transmission applications. Given an extended, uncooperative object, the AO system must create a reference wave for wavefront measurement. It does so by focusing a laser beam onto the object; therefore, creating a beacon. Unfortunately, the extended size of the beacon after propagation gives rise to speckle, causing noise in the wavefront measurements which degrades the AO system’s correction of the turbulence effects. In this paper, we use polychromatic illumination to create the reference wave, which results in an associated reduction in the speckle noise. To quantify the benefits, we use split-step wave-optics simulations with the spectral-slicing method for polychromatic light. We assume that the AO system uses a Shack Hartmann wavefront sensor. Furthermore, we assume that the speckle decorrelates over short periods of time corresponding to reasonable object motions. We consider a range of conditions for the object size (i.e. the object Fresnel number), object motion, and illuminator coherence length. The results show a reduction in the speckle-induced error with polychromatic light, especially when the object is large. This finding indicates that polychromatic illumination can improve the performance of AO systems when the object is both uncooperative and extended.

We present a fast and reconfigurable architecture of centroiding for wavefront sensing implemented in FPGA, with a short latency in the order of microseconds, due to the tight integration design of a CMOS image sensor and the FPGA, and the fast algorithm implementation. Data are processed straight away as they arrive, so there is no need to use external storage in a high capacity memory, that will generate inconvenient delays for real time applications. In this architecture data are processed in a pipeline or parallel fashion when convenient, by means of a stream processing with moving filters algorithm (SCoG), or fixed regions in the image sensor typical from a Shack-Hartmann array using the 1st Fourier Coefficient (1FC). In this work timing and performance of both algorithms are presented, as well as on-sky tests when attached to a 12-inch Meade LX200 telescope aiming for bright stars. The results show a latency no longer than 10 microseconds, for a region of 300 pixels per row in the image sensor. These architecture provide a promising solution as a part of an adaptive optics system design for astronomy and space situational awareness applications. Possible applications are astronomy and space situational awareness. We show some preliminary results for on-sky tests using these two centroiding algorithms.

We propose an optical diagnosis for plasma electron density measurement with the Coherent Modulation Imaging(CMI) method which is a kind of phase retrieval technique and doesn’t need a reference beam. The phase of the diagnostic light can be reconstructed by CMI algorithm. The distribution of electron density can be obtained by dealing with the phase change using Abelian integral formula. Experimental results showed that the area where the plasma generated is ejected from the center. As the energy of laser driver beam increases, the phase difference region resulting from the generation of the plasma becomes larger.

During propagation of the high-power laser radiation through atmosphere the quality of the beam is significantly reduced due to atmosphere turbulence. For compensation of the wavefront distortions and improving quality of radiation, as a rule, adaptive optics approaches are used. The design and main characteristics of 121-element water-cooled stacked-actuator deformable mirror for this kind of applications is discussed in this paper.

Fast adaptive optical system can be used, for example, for correction of laser beam passed through a strong turbulent atmosphere. The frequency that such a system should operate with to achieve an acceptable level of wavefront correction is about 1 - 1.5 kHz. There are two most popular methods to develop this system: by using a standard PC computer and by using FPGA. This paper presents the advantages and disadvantages of each of these approaches. The results obtained with the use of these systems are presented. Recommendation for achieving higher performance are given.

Laser beam focusing (λ = 0.65 μm) through the scattering suspension of polystyrene microspheres in distilled water was investigated. Shack-Hartmann sensor was used to measure the local slopes of the Poynting vector, the CCD camera was used to measure the far-field focal spot’s intensity. Numerical and experimental investigations of focusing efficiency of the two bimorph deformable mirrors with 14 and 48 control channels were performed.

Enhanced self-heterodyne synthetic aperture imaging ladar (SAIL) is based on the down-looking SAIL, with a transmitter of two coaxial polarization-orthogonal beams of spatial parabolic phase difference and a receiver of heterodyne detection. Enhanced self-heterodyne SAIL has the capability to eliminate the influence from the atmospheric turbulence, has a high advantage in the detection of weak signals. However, the relative movement of target and lidar platform will generate ghost image in enhanced self-heterodyne SAIL. The image process of ghost image is mathematically detailed and simulated, the results image as the theoretical analysis. The enhanced self-heterodyne SAIL is necessarily work in spotlight mode in order to eliminate ghost image for far-distance lidar imaging.

A polarized light scanning optical microscopy is an important imaging technique popular for its ability to determine the information on molecular orientation of the sample being studied. The determination of the molecular orientation directly depends on the electric field orientation around the focus of a lens, which is used to focus the light to illuminate the sample. In this paper, we present the effect on the electric field orientation at the focal plane of the lens due to the presence of a few primary optical aberration present in the light beam.

3D coherent imaging ladar based on frequency modulated continuous wave (FMCW) technology is proposed. The triangle wave is used to modulate chirped laser. The distance information is detected by optical heterodyne technique. Meanwhile, the beam scanning is realized by rotation double-prism. And the 3D target image is obtained. The 3D coherent imaging ladar has advantages of anti-background interference, high sensitivity and long-detected distance. Under the condition of the strongly sunlight background, the targets outdoor are scanned and high resolution images are achieved. This technique has a great potential for applications in extensive imaging ladar fields.

The paper presents the possibility to obtain comprehensive information on the structure of an optical field, including the field skeleton and the regions of constant phase. High accuracy of reconstruction of the phase map, as well as invariance of the phase distributions following from direct simulation provides a new algorithm for solving the inverse phase problem in optics.

An analysis of a "window" 2D/3D Hilbert transform for reconstruction of the phase distribution of the intensity of a speckle field has been carried out. It is shown that the advantage of these approaches consists in the invariance of a phase map to a change of the position of the kernel of transformation and in a possibility to reconstruct the structure forming elements of the skeleton of an optical field. Within the framework of the approach based on the use of the discrete 2D "window" Hilbert transform, we have demonstrated the feasibility for reconstructing the phase of random 2D objects in real time.

Recent advances in multiframe blind deconvolution of ground based telescopes are presented. The paper focuses on practical aspects of the software and algorithm. (1) A computer simulation that models atmospheric turbulence, noise and other aspects, for testing and evaluation of the deconvolution system are explained. (2) A post-processing algorithm that corrects for glint due to specular and other bright reflections is presented. This glint correction is automated by a spatially adaptive scheme that calculates statistics of brightness levels. (3) Efforts to realize computational speed, wherein processing happens on-the-fly at streaming frame rates are underway. The massively parallel processing of graphical processing units (GPUs) and the Compute Unified Device Architecture (CUDA) language are used.

There are lots of requirements of 3D terrain information in the field of traffic and forest investigation. In this paper we propose a coherent lidar system that produces 3D information of target by use of circularly scanning system. We use the frequency modulated continuous laser wave as optical source. The frequency information from the targets can be demodulated by the FFT algorithm to get the real distance information and generating a point cloud. The method has advantage of background noise resistance over traditional direct detection system. The demonstration system not only acquire the distance information of scanned target. It also measures the dynamic information such as speed of moving target. In our work, we measure the speed of swaying leaves of a tree within gentle breeze and the measurements are in line with the experimental environment at that time. Furthermore, a complicated demonstration system including four laser sources will be designed. More laser footprints can enlarge the scanning area at per second and mitigate modulation and demodulation stress of system, which acquires more detailed information.

In this paper, submillimeter three dimensional tomography imaging of paramagnetic contaminants flow rate in multiphase flow pipelines is presented. The device, which is based on Magnetic Particle Imaging (MPI), consists of an array of twelve coils and a pair of permanent magnets and is not influenced with the other phases that constitute the crude oil (e.g. oil, water, sand, and gas) and which are mainly diamagnetic materials. The concentration of the paramagnetic particles can be measured in a three dimensional volumetric space with high spatial and temporal sensitivities which are proportional to the strength of the applied magnetic field. This is also influenced by the size and distribution of the particles and the anisotropy of the permanent magnet. To increase the sensitivity and improve the spatio- encoding field, a two dimensional Linear Field Scanning (LFS) technique coupled with a two dimensional excitation field is proposed. The results demonstrate that the technique would constitute a breakthrough in the area of solid flow measurements and imaging.

Solid contaminants have been found to be a major obstacle in assuring the quality of flow in pipelines. The presence of these substances leads to clogging of pipes that causes serious issues downstream when transporting oil or gas. This paper suggests an Electrical Capacitance Tomography (ECT) system for real-time measurement of solid contaminants in gas pipelines. It consists of a ring of eight electrodes evenly distributed in the circular cross section of the probe. The speed-up enhancement is achieved using a Field Programmable Gate Array (FPGA) for the post-processing part of the system to accelerate the intensive matrix multiplications which are required in the image reconstruction algorithm. Experimental results on field-collected solid contaminants demonstrate the capability of the system to build in real-time two dimensional cross section images of the contaminants while giving an estimated measurement of their concentration.