System matrix generation for 3D tomographic reconstructions using an optical design software

The burgeoning field of astrophotonics, the interface between astronomy and photonics, is redefining astronomical instrumentation to replace traditional bulk optical systems with integrated optics. This drives the development of a new promising photonics-integrated interferometric imaging technique, called the segmented planar imaging detector for electro-optical reconnaissance (SPIDER). Compared to conventional imaging systems, SPIDER can reduce the size, weight, and power (SWaP) by one to two orders of magnitude for an equivalent imaging resolution in virtue of photonics-integrated technology. However, SPIDER has a dense lens distribution and tens of separated narrow wavebands demultiplexed by array waveguide gratings. In this paper, we developed a new simplified sparse-aperture photonics-integrated interferometer (SPIN) imaging system. The SPIN imaging system was no more a Michelson configuration interferometer as SPIDER and was designed as a Fizeau configuration interferometer imaging system. This transfer of configuration type affords a more concise structure; the SPIN was designed with much less apertures and fewer wavebands than those of SPIDER. Further, the SPIN yields enhanced modulation transfer function and imaging quality with equivalent aperture diameter, compared with SPIDER. The main barrier of this transfer is the elimination of coupling restriction at the tip of a waveguide, namely the apodization effect. This effect, which is caused by the coupling effect between Fourier lens and waveguide, hinders SPIN imaging systems from getting finer resolution. However, a microscope could be used to eliminate this effect. Moreover, a waveguide array is used to receive these finer details and enlarges the field of view in SPIN. The coupling efficiency of the waveguides and crosstalk errors between waveguides of array were analyzed, which are important for proper parameters setting in SPIN imaging system. Based on these analyses, the imaging principle was derived and a hyper-Laplacian-based imaging reconstruction algorithm was developed. A simulation of the SPIN imaging system with seven apertures and one imaging waveband demonstrated the high imaging quality.

Snapshot microlens array microscopic hyperspectral imaging systems do not require a scanning process and obtain (x,y,λ) three-dimensional data cubes in one shot. Currently, the three-dimensional spectra image data are interleaved on a charge-coupled device detector, which increases subsequent data processing difficulty. The optical design software cannot simulate actual engineering installation and adjustment results accurately and the tracking results cannot guide precise rapid online calibration of the snapshot microlens array microscopic hyperspectral imaging system. To solve these problems, we propose an accurate spectral image reconstruction model based on optical tracing, derive spatial dispersion equations for the prisms and gratings, establish an algorithm model for the correspondence between the microlens array's surface dispersion spectral distribution and its imaging position, and propose a three-dimensional spectral image reconstruction algorithm. Experimental results show that this algorithm's actual spectral calibration error is better than 0.2 nm. This meets the image processing requirements of snapshot microlens array microscopic hyperspectral systems.

Resolution enhanced 3D image reconstruction by use of ray tracing and auto-focus in computational integral imaging

Active Terahertz-wave imaging systems play a significant role in security and surveillance applications. This paper describes a 0.14THz near-field imaging system, which consists of a signal generator and acquisition unit, a transceiver front end, a digital signal process unit and a motor control unit. Base on the two-dimensional synthetic aperture technique and the image reconstruction algorithm, this system is capable of producing three-dimensional images of 2mm lateral resolution and 3cm range resolution in concealed weapon detection experiments.

In this paper, we demonstrate light field triangulation to determine depth distances and baselines in a plenoptic camera. Advances in micro lenses and image sensors have enabled plenoptic cameras to capture a scene from different viewpoints with sufficient spatial resolution. While object distances can be inferred from disparities in a stereo viewpoint pair using triangulation, this concept remains ambiguous when applied in the case of plenoptic cameras. We present a geometrical light field model allowing the triangulation to be applied to a plenoptic camera in order to predict object distances or specify baselines as desired. It is shown that distance estimates from our novel method match those of real objects placed in front of the camera. Additional benchmark tests with an optical design software further validate the model’s accuracy with deviations of less than ±0.33% for several main lens types and focus settings. A variety of applications in the automotive and robotics field can benefit from this estimation model.

Abstract. As remote sensing and variable-rate technology are becoming more available for aerial applicators, practical methodologies for effective integration of these technologies are needed for site-specific aerial applications of crop production and protection materials. The objectives of this study were to demonstrate how to integrate an airborne multispectral imaging system and an IntelliStar variable-rate aerial application system for site-specific management of the winter weed henbit. The airborne imaging system was used to acquire natural color and near-infrared (NIR) images of a fallow field near College Station, Texas, for mapping the infestation of henbit shortly before herbicide application. The images were then rectified, classified, and converted to a binary prescription map with the full application rate on infested areas and the zero rate on non-infested areas. The variable-rate aerial application system mounted on an agricultural aircraft was used to apply glyphosate over the field based on the prescription map. Airborne imagery was collected 14 days after the herbicide application. The as-applied map along with the prescription map and the post-application imagery were used to assess the performance of the site-specific application. Spatial and statistical analysis results showed that the imaging system was effective for mapping henbit infestations and for assessing the performance of site-specific herbicide application, and that the variable-rate system accurately delivered the product at the desired rate to the prescribed areas for effective control of the weed. The methodology and results from this study will be useful for aerial applicators to incorporate airborne imaging and variable-rate application systems into their aerial application business to increase their capabilities and profits. Keywords: Aerial application, As-applied map, Henbit, Imaging system, Prescription map, Variable-rate technology.

Millimeter-wave holographic imaging techniques have recently been developed for personnel surveillance applications at airports and other high-security checkpoints. Millimeter- wave imaging is useful for this application since millimeter-waves easily pass through common clothing materials yet are reflected from the human body and any items concealed by clothing. This allows a high-resolution imaging system to form an image revealing items concealed on the person imaged. A prototype imaging system developed at Pacific Northwest National Laboratory uses a scanned linear array of millimeter-wave antennas to capture wideband millimeter-wave data in approximately one second. This data is then mathematically reconstructed to form a high- resolution 3D image of the person being scanned. Millimeter- wave imaging has been demonstrated to be effective for detecting concealed weapons on personnel. Another imaging technique which could be applied to the weapon detection problem is acoustic imaging. Like millimeter-waves, ultrasonic acoustic waves can also penetrate clothing, and can be used to form relatively high-resolution images which can reveal concealed weapons on personnel. Acoustic imaging results have been obtained using wideband holographic imaging techniques nearly identical to the imaging techniques used for millimeter-wave imaging. Preliminary imaging results at 50 kHz indicate that acoustic imaging can be used to penetrate some types of common clothing materials. Hard clothing materials, such as leather on vinyl, are essentially opaque to acoustic waves at 50 kHz. In this paper, millimeter-wave and acoustic wave imaging techniques are compared for their effectiveness and suitability in weapon detection imaging systems. Experimental results from both imaging modalities are shown.

We present algorithms for polarization ray tracing through uniaxial optically active crystals, such as quartz, in a form specifically suited for integration into optical design software. These algorithms incorporate ray directions, polarization modes, optical path lengths, and Fresnel transmission and reflection equations. Current commercially available polarization ray tracing software does not perform birefringent ray tracing in uniaxial or optically active materials. The optical designer lacks a straightforward tool for analyzing propagation and aberrations in these media. We apply these algorithms to some examples. For a quartz polarization rotator a misalignment of the crystal axis of 1° is negligible, but a misalignment of 5° renders the device useless.

Numerical studies were performed to evaluate and compare four different algorithms for tomographically reconstructing pollutant concentrations in indoor air measured with an optical remote sensing system. With a remote sensing/computed tomography system, two-dimensional maps of air concentrations can be created for an entire room with good spatial and temporal resolution. The success of such a system for characterizing the flow of contaminants in air, exposure assessment, and leak detection depends on the choice of tomographic reconstruction algorithm. A systematic method was developed to evaluate the performance of four algorithms: ART, ART3, SIRT, and SART. One hundred and twenty test maps were reconstructed by each algorithm under ideal and nonideal sampling conditions, and image quality was evaluated using four criteria. The nonideal sampling conditions included simulation of measurement noise and reduction in the number density of rays. Performance of the algorithms was found to be intimately related to the number of peaks in the test maps. The importance of using multiple measures of image quality was underscored by the fact that for some sampling conditions simulated, performance of the algorithms was judged differently depending on the evaluation criteria. Results indicated that using numerical studies is successful for evaluating such algorithms.

Phase-Contrast Tomography (PCT) is becoming an important technique for nondestructive, in-situ characterization of soft and hard condensed matter. This thesis sheds light on our progress in developing novel tomographic reconstruction algorithms in combination with in-situ experimental approaches that employ propagation-based PCT. These developments are aimed to improve the spatial and temporal resolutions of in-situ studies of the soft and hard condensed matter. The mechanical properties of materials such as steel are, to a large extent, defined by its microstructure. Propagation-based PCT (i.e. holotomography) can be used to visualize the microstructures associated with small variations in density or composition in the bulk of the specimen. This imaging technique has the advantage of being non-destructive and allows to carry out in-situ, time-resolved observations of miscrostructural changes during dynamic processes such as solid-state phase transformations. Sufficient spatial and temporal resolution can be achieved only when an extremely bright x-ray source is used. In order to test whether a novel table-top x-ray source, the MIRRORCLE-6X, can be used for implementation of a propagation-based PCT system, we have carried out a series of experiments. The characteristics of a propagation-based PCI system that employs the MIRRORCLE-6X were analyzed. In our further research we have focused on the experiments that could be performed at the European Synchrotron Radiation Facility (ESRF) in Grenoble, France. We reported on the investigation of the cementite microstructure in carbon steel. In this work we present the reconstruction of the three-dimensional morphology of cementite grains in the bulk of steel using a non-destructive imaging technique – x-ray Phase-Contrast Tomography (PCT). Complementary information about the crystalline structure of the ferrite grains surrounding the cementite is obtained using x-ray Diffraction-Contrast Tomography (DCT). The work was continued by a time-resolved x-ray PCT investigation of the austenite grain growth during the ferrite-to-austenite phase transformation in low-carbon steel. Experimental data allows to visualize the evolution of the three-dimensional morphology of the austenite-ferrite interfaces with a spatial resolution on the order of 1 ?m and a time resolution of less than 9 minutes. The in-situ measurements show that the theory for grain growth during diffusional solid-state phase transformations needs to be extended in order to describe the drastically lower mobility that we observed for flat interfaces compared to curved interfaces. We observe that some flat interfaces are completely immobile, which is not predicted by the state-of-the-art theories and showed - for the first time - that new computational model for grain growth are needed. Quantitative image reconstruction based on PCT data requires solving two inverse problems: phase retrieval and tomographic reconstruction. In most cases, the problem of phase retrieval is ill-posed and requires that some type of a prior knowledge about the reconstructed image (i.e. particular regularization method) is used. We present a novel algebraic approach suitable for phase retrieval using various linear models. In this approach Total Variation (TV) minimization is used for regularization of the linearized inverse problem by promoting the solution with a sparse gradient magnitude (i.e. piece-wise constant solution). In that case prior knowledge about the reconstructed image may allow to (partially) recover the unknown spatial frequencies that are undefined by the experimental data. The problem of tomographic reconstruction based on PCT data can be solved using a similar approach. We conclude our investigation of the image reconstruction algorithms by introducing several algebraic approaches suitable for tomographic reconstruction based on PCT data. In these approaches TV minimization is used to find a regularized solution to an underdetermined linear system based on a linearized representation of the PCT. When the density of the reconstructed object is piece-wise constant (or close to it) a virtually artifact-free solution can be computed for the tomographic problem. The proposed approach can also be used to radically improve the accuracy of the tomographic reconstruction based on incomplete data (e.g. small number of projections) or data with low signal to noise ratio.

A novel 3D reconstruction and fast imaging system for subcutaneous veins by augmented reality is presented. The study was performed to reduce the failure rate and time required in intravenous injection by providing augmented vein structures that back-project superimposed veins on the skin surface of the hand. Images of the subcutaneous vein are captured by two industrial cameras with extra reflective near-infrared lights. The veins are then segmented by a multiple-feature clustering method. Vein structures captured by the two cameras are matched and reconstructed based on the epipolar constraint and homographic property. The skin surface is reconstructed by active structured light with spatial encoding values and fusion displayed with the reconstructed vein. The vein and skin surface are both reconstructed in the 3D space. Results show that the structures can be precisely back-projected to the back of the hand for further augmented display and visualization. The overall system performance is evaluated in terms of vein segmentation, accuracy of vein matching, feature points distance error, duration times, accuracy of skin reconstruction, and augmented display. All experiments are validated with sets of real vein data. The imaging and augmented system produces good imaging and augmented reality results with high speed.

Ionospheric tomography is a technique whereby a vertical cross section through ionospheric electron density can be imaged. The vertical resolution of ionospheric tomography systems is inherently poor, but can be improved by using a priori information in the tomographic reconstruction algorithm. Care must be exercised in using a priori information, since if too much of it is used, the reconstruction algorithm may discard some of the information contained in the tomographic data in favor of satisfying some of the a priori assumptions. Orthogonal decomposition (OD) is an existing technique that uses a priori information to constrain the reconstruction to lie in a space of reasonable images without weighting the reconstruction toward any particular a priori image. In this way a priori information can be used in a manner that does not overwhelm information contained in the data. Gauss-Seidel (GS) is an iterative algorithm that is used to calculate solutions for large systems of linear equations. In this article, a block version of the GS algorithm will be used to calculate the solution of the least-squares problem that is created using OD. The complete algorithm presented here will be called the residual correction method (RCM), since it involves calculation of successively better approximations based on the residual error. RCM is a fast and numerically stable algorithm that extracts as much information from the data as possible. A numerical example demonstrating the properties of RCM will also be presented. © 1996 John Wiley & Sons, Inc.

Medical images are acquired for the purpose of gathering information regarding the disease state of a patient. The quality of the image should be a measure of how a specified task may be performed given the resulting image. Image quality is task dependent; one imaging system may provide images that allow better task performance than another system's for one task, but worse for another task. Determining the quality of an imaging system involves specifying the task of interest, the range of objects that will be imaged, and the observer (human or machine reader) who will perform the task. In radiography it has become common to use Fourier measures to describe image quality through a combination of Fourier‐based measures of system resolution and noise. The Line Spread Function, when Fourier transformed, yields the Modulation Transfer Function (MTF) as a measure of system resolution. Use of the MTF to describe a system's resolution is appropriate when the imaging system is shift‐invariant, that is, the line spread function is independent of position. Image noise is described in the Fourier domain by the Noise Power Spectrum (NPS). We can use the NPS to describe the noise in an imaging system whenever the noise properties are stationary, meaning that the variance and correlations between fluctuations in different locations are not dependent on their absolute location. These Fourier measures of system resolution and noise are commonly combined to give an overall figure of merit known as the Detective Quantum Efficiency (DQE). The DQE describes the signal‐to‐noise transfer characteristics of an imaging system as long as those assumptions of shift‐invariance and noise stationarity are valid. In digital systems the image of an object is affected by the location of the object with respect to the pixel grid. In other words, the detector pixels cause the system to be shift‐variant. In this case the MTF does not describe the resolution properties completely. This is particularly the case for tomographic systems, where the point‐response function is quite position‐dependent. Moreover, in real imaging systems the noise properties will depend on position, most notably because real patients always have structure. So, the Fourier‐domain noise concept of Noise Power Spectrum does not capture all the properties of noise for real imaging systems and tasks. In this talk we will consider a general treatment of the imaging system as a mapping of information from the patient to the data, without the assumptions inherent in Fourier analysis. We will discuss approaches to the characterization of system resolution and noise in terms of position‐dependent parameters. Once such position‐dependent imaging properties of a system are determined, we can use them to calculate measures of image quality that summarize the usefulness of the images for the performance of various visual tasks.

A simple multispectral classification method for the identification of systemically diseased chickens was developed and tested between two different imaging systems. An image processing algorithm was developed to define and locate the region of interest (ROI) as classification areas on the image. The average intensity was calculated for each classification area of the chicken image. A decision tree algorithm was used to determine threshold values for each classification areas. The wavelength of 540 nm was used for image differentiation purpose. There were 164 wholesome and 176 systemically diseased chicken images collected using the first imaging system, and 332 wholesome and 318 systemically diseased chicken images taken by the second imaging system. The differentiation thresholds, generated by the decision tree method, based on the images from the first imaging system were applied to the images from the second imaging system, and vice versa. The accuracy from evaluation was 95.7% for wholesome and 97.7% of systemically diseased chickens for the first image batch, and 99.7% for wholesome and 93.5% for systemically diseased chickens for the second image batch. The result showed that using single wavelength and threshold, this simple classification method can be used in automated on-line applications for chicken inspection.

Imaging systems using aspheric imaging lenses with complementary computation can deliver performance unobtainable in conventional imaging systems. These new imaging systems, termed Wavefront coded imaging systems, use specialized optics to capture a coded image of the scene. Decoding the intermediate image provides the "human-usable" image expected of an imaging system. Computation for the decoding step can be made completely transparent to the user with today's technology. Real-time Wavefront coded systems are feasible and cost-effective. This "computational imaging" technology can be adapted to solve a wide range of imaging problems. Solutions include the ability to provide focus-free imaging, to increase the field of view, to increase the depth of read, to correct for aberrations (even in single lens systems), and to account for assembly and temperature induced misalignment. Wavefront coded imaging has been demonstrated across a wide range of applications, including microscopy, miniature cameras, machine vision systems, infrared imaging systems and telescopes.