This PDF file contains the front matter associated with SPIE Proceedings Volume 9846, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and Conference Committee listing.

Using the brightness function imaging approach we analyze the impact of the desert and ocean type inverse temperature layer (ITL) on the modulation transfer function (MFT) of an incoherent imaging system. It is shown that an ITL located in vicinity of an imaging path can result in nonlinear deviation in imaging of an object spatial spectrum. Using periodical (sine) patterns of different spatial frequencies as an object, we show that presence of an ITL leads to formation of images with a broadened spatial spectrum with shifted frequency of the sine pattern image in respect to object frequency. The image spectrum shift and width depend on the ITL characteristics and its location in respect to optical wave propagation path. The observed changes in the sine pattern spectral content represent a challenge for analysis of imaging systems performance using conventional MTF based framework. We also analyzed impact of atmospheric turbulence on imaging of periodical (sine) patterns and compared this with the known theoretical results.

Phase screen-based wave optics simulations are a fundamental tool used by researchers seeking to understand the effect of atmospheric turbulence on laser beam propagation and imaging. Most wave optics packages are either themselves proprietary or rely on expensive, proprietary software packages. We have developed WavePy, a wave optics package based in the open-source Python programming environment. Using WavePy we have been able to produce turbulence-corrupted imagery similar to those observed by ground-based telescopes imaging space objects. We have also simulated plane wave and spherical wave propagation through uniform turbulence volumes. In both cases, we found the execution time between the WavePy and MATLAB versions to be similar under certain circumstances.

Computational efficiency and accuracy of wave-optics-based Monte-Carlo and brightness function numerical simulation techniques for incoherent imaging through atmospheric turbulence are evaluated. Simulation results are compared with theoretical estimates based on known analytical solutions for the modulation transfer function of an imaging system and the long-exposure image of a Gaussian-shaped incoherent light source.

Differential tilt variance is a useful metric for interpreting the distorting effects of turbulence in incoherent imaging systems. In this paper, we compare the theoretical model of differential tilt variance to simulations. Simulation is based on a Monte Carlo wave optics approach with split step propagation. Results show that the simulation closely matches theory. The results also show that care must be taken when selecting a method to estimate tilts.

Range-gated imaging systems are active systems which use a high-power pulsed-light source and control the opening and closing times of the camera shutter in conjunction with the light source. By calculating the arrival time of the reflected light from the object, the camera shutter is opened for a short time period to form an image using the returned light. This allows generating high contrast images of the objects in difficult lighting conditions. On the other hand the object distance needs to be known and operators are expected to select the proper shutter timing to keep the object of interest continuously in the view. In order to automate this procedure, a tracking system needs to provide feedback to adjust camera shutter timing by estimating the distance of the object in addition to its horizontal and vertical position. In this paper, we present an object tracking framework integrated to the range-gated camera setup without resorting to an additional laser or radar based range finder unit even the object distance changes during the tracking. Range estimation is solely based on image processing and the distance of the object is estimated by the proposed algorithm with a number of similarity measurement methods. The performances of these methods are compared for various scenarios using the data acquired by the range-gated system setup.

Canopy distortion occurs when a pilot is looking through any curved aircraft transparency. Any helmet mounted display system must either compensate for this distortion, or incur canopy distortion error in its total error budget. Thales Visionix has applied a novel method for characterization of and compensation for aircraft canopy distortion, allowing for views from any position within a large head box. We present techniques allowing for compensation of canopy distortion for the entire HMD head-box, and implications observed based on applying these techniques for A- 10 and F-16 canopies

When capturing image data over long distances (0.5 km and above), images are often degraded by atmospheric turbulence, especially when imaging paths are close to the ground or in hot environments. These issues manifest as time-varying scintillation and warping effects that decrease the effective resolution of the sensor and reduce actionable intelligence. In recent years, several image processing approaches to turbulence mitigation have shown promise. Each of these algorithms have different computational requirements, usability demands, and degrees of independence from camera sensors. They also produce different degrees of enhancement when applied to turbulent imagery. Additionally, some of these algorithms are applicable to real-time operational scenarios while others may only be suitable for post-processing workflows. EM Photonics has been developing image-processing-based turbulence mitigation technology since 2005 as a part of our ATCOM [1] image processing suite. In this paper we will compare techniques from the literature with our commercially available real-time GPU accelerated turbulence mitigation software suite, as well as in-house research algorithms. These comparisons will be made using real, experimentally-obtained data for a variety of different conditions, including varying optical hardware, imaging range, subjects, and turbulence conditions. Comparison metrics will include image quality, video latency, computational complexity, and potential for real-time operation.

This research project aims to provide a software framework to test and simulate optimization algorithms for a phase locked fiber laser array. The adaptive phase coherent fiber laser array system is a prominent innovation in the areas of optical communications and directed energy projection [1][2]. In comparison with a monolithic large aperture system, the phase locked array exhibits dramatic improvements in cost, size, and energy density at the center of the beam [2].

High quality linear laser frequency chirp of high chirp rate is critical to many laser ranging applications. In this paper, we describe a cost-effective chirp linearization approach implemented on our Inverse synthetic Aperture LADAR (ISAL) imaging testbed. Our approach uses a COTS PZT for external cavity laser frequency tuning and a common self-heterodyne fiber interferometer as a frequency monitor, with a two-step hardware and software chirp linearization procedure to achieve high quality chirp. First, the nominal triangle waveform input to PZT drive is modified through an iterative process prior to ISAL imaging acquisition. Several waveforms with chirp rates between 1 and 4THz/s have been acquired with residual chirp rate error ~ +/-2% in usable region. This process generally needs to be done only once for a typical PZT that has excellent repeatability but poor linearity. The modified waveform is then used during ISAL imaging acquisition without active control while the imperfection in transmitted frequency is monitored. The received imaging data is resampled digitally based on frequency error calculated from the frequency monitor data, effectively reduce chirp nonlinearity to ~+/- 0.2% in chirp rate error. The measured system impulse response from return signal shows near designed range resolution of a few mm, demonstrating the effectiveness of this approach.

An Inverse Synthetic Aperture LADAR (ISAL) system is capable of providing high resolution surface mapping of near Earth objects which is an ability that has gained significant interest for both exploration and hazard assessment. The use of an ISAL system over these long distances often presents the need to operate the optical system in photon-starved conditions. This leads to a necessity to understand the implications of photon and detector noise in the system. Here a Carrier-to-Noise Ratio is derived which is similar to other optical imaging CNR definitions. The CNR value is compared to the quality of experimentally captured images recovered using the Phase Gradient Autofocus technique both with and without the presence of atmospheric turbulence. A minimum return signal CNR for the PGA to work is observed.

As airborne EOIR imaging systems strive to achieve high-NIIRS full motion video (FMV) from longer and longer standoff ranges, the challenges behind conceptualizing, designing, and fielding such systems grows significantly. We present a heuristic framework for dissecting the "goodness" of an FMV multispectral sensor and look at the various components behind what makes a high-resolution sensor. Combining spatial, temporal, spectral, and "signal" resolution with system footprint size/weight/power (SWaP) metrics allows deterministic tradeoffs between optical systems as well as system architectures. We present example trade studies of optical architectures from disparate application fields in various SWaP-constrained environments for long-range imaging and evaluating how system parameters are intrinsically linked.

Hyperspectral Imaging (HSI) is finding utility in many new areas, such as environmental and agricultural monitoring, medicine and food technology, industrial inspection, land management, and defense usage, due to its ability to simultaneously collect both spatial and spectral information. Within the tropical environment the utility of HSI has been demonstrated through various rain forest and coastal environmental programs.

System performance for all HSI systems is influenced by many factors, including environmental conditions, operational usage, internal system composition and the processing chain. Truly optimizing this performance requires an understanding of the operational conditions under which each system will perform. One of the key factors affecting system performance, especially at long stand-off ranges, is the atmospheric effects. This paper presents analytical results demonstrating the effects of atmospheric conditions on long stand-off airborne HSI systems based on a Raytheon developed performance model for estimating System performance.

This end-to-end System Performance Model is especially designed for long stand-off airborne detection with large off-nadir viewing angles. It takes into account most of the components within the entire imaging chain. The model divides the end-to-end imaging chain into three parts: the environmental component, the Concept of Operations (CONOPS), and the imaging system effects. The environmental component includes solar illumination, reflectance of materials on the ground, scattering, and atmospheric transmittance. The system component includes the effects of system noise and throughput. The CONOPS accounts for the various operating conditions best suited for long stand-off detection. The analytical results presented in this paper provide details on the influence of the atmospheric conditions, including tropical conditions, on NESR and SNR performance in a Spot Mode CONOPS for a HSI system based on the end-to-end System Performance Model. These results are based on continued work developed from the “Long stand-off Performance Modelling of HSI Airborne Imaging Systems”.

A new Shack-Hartmann(S-H) spot detection algorithm was proposed in this paper for finding the location coordinates of S-H reference wavefront spot in dependent of lenslet shapes, rotational alignment error of lenslet, reference laser beam shape. It consists of five main processing module: 1) Parameter setting, 2) Noise measurement & compensation, 3) Segmentation, 4) Coarse localization, 5) Fine localization. Through some simulated experiments, the proposed algorithm showed that it could robustly detect a variety of S-H spot patterns e.g. rectangular shape, triangular shape, sandglass shape, X-shape, center-void shape, rotated rectangular shape. The detection precision of the proposed algorithm was measured with the root squared sum of the estimated coordinates difference with values less than 10^-4 pixel till signal to noise ratio S/N=3. It is firstly intended for application of infrared S-H sensor but can be adopted in visible S-H sensor.