This PDF file contains the front matter associated with SPIE Proceedings Volume 7662, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

Utilization of Near-Infrared (NIR) spectral features in a muzzle flash will allow for small arms detection using low cost silicon (Si)-based imagers. Detection of a small arms muzzle flash in a particular wavelength region is dependent on the intensity of that emission, the efficiency of source emission transmission through the atmosphere, and the relative intensity of the background scene. The NIR muzzle flash signature exists in the relatively large Si spectral response wavelength region of 300 nm-1100 nm, which allows for use of commercial-off-the-shelf (COTS) Si-based detectors. The alkali metal origin of the NIR spectral features in the 7.62 × 39-mm round muzzle flash is discussed, and the basis for the spectral bandwidth is examined, using a calculated Voigt profile. This report will introduce a model of the 7.62 × 39-mm NIR muzzle flash signature based on predicted source characteristics. Atmospheric limitations based on NIR spectral regions are investigated in relation to the NIR muzzle flash signature. A simple signal-to-clutter ratio (SCR) metric is used to predict sensor performance based on a model of radiance for the source and solar background and pixel registered image subtraction.

The Federal Aviation Administration (FAA) is presently engaged in research to quantify the visibility of aircraft under two important scenarios: aircraft observed directly by human operators in air traffic control towers (ATCT's), and aircraft observed by human operators through unmanned aerial vehicle (UAV) sensors viewed through ground-based display systems. Previously, an ATCT visibility analysis software tool (FAA Vis) was developed by the U.S. Army Research Laboratory (ARL) in collaboration with the U.S. Army's Night Vision and Electronic Sensors Directorate (NVESD) and the FAA. This tool predicts the probability of detection, recognition, and identification of various aircraft by human observers as a function of range and ATCT height. More recently, a baseline version of a UAV See-And- Avoid visibility analysis software tool was also developed by ARL, again in collaboration with NVESD and the FAA. Important to the calibration of these tools is the empirical determination of target discrimination difficulty criteria. Consequently, a set of human perception experiments were designed and conducted to empirically determine the target recognition and identification discrimination difficulty criteria for a representative set of aircraft. This paper will report on the results and analyses of those experiments.

An international group consisting of several NATO nations participated in a trial in which urban camouflage was developed and compared. First, photographs were taken in and around a small town (arid climate). Next, the different groups derived urban camouflage patterns from these photographs. We applied our method for deriving a camouflage pattern from a set of (characteristic) background images to the imagery. Eleven different patterns were made into prototype camouflage suits. Panoramic images of all prototype suits were taken on 36 locations in the environment in which the background images were taken. We used these images in a search experiment with human observers for evaluating camouflage performance of the various patterns. The pattern we developed featured among the two best performing patterns, with good performance indicated by low chance of detection and long search times. The results show that our method for deriving a camouflage pattern from background imagery works well.

Active imaging systems, including laser range-gated short wave infrared (LRG SWIR) systems, are currently being developed to increase the identification range performance of ground-to-ground electro-optical targeting systems. These systems have several distinct technological and practical advantages over passive systems, but they also suffer from peculiar phenomena, including laser speckle. This paper reports on a study in which the benefits of speckle reduction techniques on the ability of observers to identify human activities were determined empirically. Since no suitable LRG SWIR imagery existed, it was necessary to first develop a simulation of speckle formation in a typical LRG SWIR imager, which also included the chosen speckle reduction techniques. The simulation was then applied to a human activities target set and the resulting imagery evaluated in a perception experiment.

Recently new techniques for night-vision cameras are developed. Digital image-intensifiers are becoming available on the market. Also, so-called EMCCD (electro-magnified) cameras are developed, which can also record imagery in dim conditions. In this paper we present data recorded with both types of cameras (image-intensifiers and EMCCD cameras) in dim light conditions, and present the results of image enhancement on this data. The image enhancement techniques applied are noise reduction, super-resolution reconstruction and local adaptive contrast enhancement. Comparing the results from both cameras indicates that the image intensifier performs better at the dim conditions and the EMCCD camera performs somewhat better at the bright conditions.

In this paper we will address the basic performance characteristics of high performance AMLCD panels, the challenges and opportunities presented by the analog to digital acquisition process and the methods that can be used to produce maximum dynamic range and spatial resolution from IR sensor images. With the right methods and design considerations a system that can rival analog CRT performance and can certainly outperform LCDs of even a few years ago.

The Night Vision and Electronic Sensors Directorate's current time-limited search (TLS) model, which makes use of the targeting task performance (TTP) metric to describe image quality, does not explicitly account for the effects of visual clutter on observer performance. The TLS model is currently based on empirical fits to describe human performance for a time of day, spectrum and environment. Incorporating a clutter metric into the TLS model may reduce the number of these empirical fits needed. The masked target transform volume (MTTV) clutter metric has been previously presented and compared to other clutter metrics. Using real infrared imagery of rural images with varying levels of clutter, NVESD is currently evaluating the appropriateness of the MTTV metric. NVESD had twenty subject matter experts (SME) rank the amount of clutter in each scene in a series of pair-wise comparisons. MTTV metric values were calculated and then compared to the SME observers rankings. The MTTV metric ranked the clutter in a similar manner to the SME evaluation, suggesting that the MTTV metric may emulate SME response. This paper is a first step in quantifying clutter and measuring the agreement to subjective human evaluation.

Analytical Model 1 describes how long it takes the first observer to find a target when multiple observers search a field of regard using imagery provided by a single sensor. This model, developed using probability concepts, suggests considerable benefits accrue from collaborative search: when P is near one and with ten observers the mean detection time (in reduced time) is reduced by almost an order of magnitude when compared to that of a single observer. To get the instant of detection in clock time we add the delay time td to the reduced time. Empirical fits for t_d and are also given in the paper. Model 1 was verified/validated by computer simulation and perception experiments. Here ten observers searched sixty computer generated fields of regard (each one was 60 x 20 degrees) for a single military vehicle. Analytical Model 2 describes how the probability of target acquisition increases with the number of observers. The results of Model 2 suggest that probability of target acquisition increases considerably when multiple observers independently search a field of regard. Model 2 was verified by simulation but not by perception experiment. Models 1 and 2 are pertinent to development of search strategies with multiple observers and are expected to find use in wargaming for evaluating the efficacy of networked imaging sensors.

A perception experiment was performed in an effort to measure the effect of clutter on search performance while keeping target size, target contrast, and system bandwidth constant. In the NVESD time-limited search (TLS) model, detection performance is said to only vary with changes in target size and target-to-background contrast, if the imaging system and the search time limit are left constant^4,8. The results of this experiment show that changes in scene clutter produce changes in detection performance when these other factors remain unchanged, thereby making a stronger case for the inclusion of a clutter metric into the NVESD TLS model. When using real imagery, it is difficult to find good examples of change in clutter without changes in target size, contrast, noise, or other factors also being present. Using computer generated imagery of triangles and tilted squares allowed the clutter aspect of search to be experimentally isolated. When applied to imagery in the perception experiment, the masked target transform volume clutter metric was shown to correlate well with the average observer response time.

This paper presents an image-based model for target identification performance. This model is intended as an alternative to existing linear models such as NVThermIP. The image-based model allows arbitrary non-linear image processing to be applied to actual images which are compared using a human perception model. This model simulates an image from a given sensor and compares the simulated image to a reference high-quality image. For a given target set, the imagebased model generates a confusion matrix which is used to calculate the average probability of identification. The perception metric used to compare the images is a multiscale version of the SSIM. The output of the image-based model is reasonably close to the output of the NVThermIP theory when tested on a standard linear sensor system. The output also agrees well with data from a human perception test.

Moving imagery from a static scene was recorded with an un-cooled thermal imager at nine different angular velocities ranging from 0 (static) to 1 pixel/frame (3.75 deg/s) using a tilted rotating mirror. The scene contained a thermal acuity test chart with triangular test patterns based on the Triangle Orientation Discrimination (TOD) test method. The imagery was processed with different types of image enhancement: DSR (Dynamic Super Resolution), LACE (Local Adaptive Contrast Enhancement) and combinations. DSR shows a significant performance improvement at low velocities, a moderate improvement at medium velocities where smear becomes apparent and no benefit at high speed. Performance with LACE is close to optimized gain and level setting by hand. Static performance and dynamic performance at 0.57 pixel/frame containing significant smear were compared with earlier published identification performance data for twohand held systems collected under a variety of signal processing conditions. It shows that the ratio M75 between the 75% correct threshold size for the two-hand held objects and the TOD triangle is preserved under all conditions measured. Thus, TA range prediction based on the TOD is robust against a complex combination of conditions, including motion, smear and the types of image enhancement applied.

The next generation of Army imager performance models is currently under development at NVESD. The aim of this new model is to provide a flexible and extensible engineering tool for system design which encapsulates all of the capabilities of the existing Night Vision model suite (NVThermIP, SSCamIP, etc) along with many new design tools and features including a more intuitive interface, the ability to perform trade studies, and a library of standard and user generated components. By combining the previous model architectures in one interface the new design is better suited to capture emerging technologies such as fusion and new sensor modalities. In this paper we will describe the general structure of the model and some of its current capabilities along with future development plans.

Modern space based optical sensors place substantial demands on the focal plane array readout integrated circuit. Active pixel readout designs offer direct access to individual pixel data but require analog to digital conversion at or near each pixel. Thus, circuit designers must create precise, fundamentally analog circuitry within tightly constrained areas on the integrated circuit. Rapidly changing phenomena necessitate tradeoffs between sampling and conversion speed, data precision, and heat generation adjacent the detector array, especially of concern for thermally sensitive space grade infrared detectors. A simplified parametric model is presented that illustrates seeker system performance and analog to digital conversion requirements trends in the visible through mid-wave infrared, for varying sample rate. Notional limiting-case Earth optical backgrounds were generated using MODTRAN4 with a range of cloud extremes and approximate practical albedo limits for typical surface features from a composite of the Mosart and Aster spectral albedo databases. The dynamic range requirements imposed by these background spectra are discussed in the context of optical band selection and readout design impacts.

Meticulous experimental design may not always prevent confounds from affecting experimental data acquired during visual perception experiments. Although experimental controls reduce the potential effects of foreseen sources of interference, interaction, or noise, they are not always adequate for preventing the confounding effects of unforeseen forces. Visual perception experimentation is vulnerable to unforeseen confounds because of the nature of the associated cognitive processes involved in the decision task. Some confounds are beyond the control of experimentation, such as what a participant does immediately prior to experimental participation, or the participant's attitude or emotional state. Other confounds may occur through ignorance of practical control methods on the part of the experiment's designer. The authors conducted experiments related to experimental fatigue and initially achieved significant results that were, upon re-examination, attributable to a lack of adequate controls. Re-examination of the original results and the processes and events that led to them yielded a second experimental design with more experimental controls and significantly different results. The authors propose that designers of visual perception experiments can benefit from planning to use a test-fix-test or adaptive experimental design cycle, so that unforeseen confounds in the initial design can be remedied.

Operating environments that US Soldiers and Marines are in have changed, along with the types of tasks that they are required to perform. In addition, the potential imaging sensor options available have increased. These changes make it necessary to examine how these new tasks are affected by waveband and time of day. US Army Research, Development and Engineering Command, Communications Electronics Research Development and Engineering Center, Night Vision and Electronic Sensor Directorate (NVESD), investigated one such task for several wavebands (MWIR, LWIR, Visible, and SWIR) and during both day and night. This task involved identification of nine different personnel targets: US Soldier, US Marine, Eastern-European/Asian Soldier, Urban Insurgent, Rural Insurgent, Hostile Militia, Indigenous Inhabitant, Contract Laborer, and Reporter. These nine distinct targets were made up from three tactically significant categories: Friendly Force, Combatant and Neutral/Non-Combatant. A ten second video was taken of an actor dressed as one of these targets. The actors walk a square pattern, enabling all aspects to be seen in each video clip. Target characteristics were measured and characteristic dimension, target contrast tabulated. A nine-alternative, forced-choice human perception test was performed at NVESD. This test allowed NVESD to quantify the ability of observers to discriminate between personnel targets for each waveband and time of day. The task difficulty criterion, V50, was also calculated allowing for future modeling using the NVESD sensor performance model.

Often various amounts of complementary information exist when imagery of the same scene is captured in different spectral bands. Image fusion should merge the available information within the source images into a single fused image that contains more relevant information compared to any single source image. The benefits of image fusion are more readily seen when the source images contain complementary information. Intuitively complementary information allows for measurable improvements in human task performance. However, quantifying the effect complementary information has on fusion algorithms remains open research. The goal of this study is to quantify the effect of complementary information on image fusion algorithm performance. Algorithm performance is assessed using a new performance metric, based on mutual information. Human perception experiments are conducted using controlled amounts of complementary information as input to a simple fusion process. This establishes the relationship between complementary information and task performance. The results of this study suggest a correlation exists between the proposed metric and identification task performance.

This work provides an answer to the question "How good does the image need to be?" for testing image quality of fire service thermal imagers. Fire fighters were asked to identify potential fire hazards in 4500 images that had been degraded in brightness, contrast, spatial resolution, and noise level. A perception model was built from the resulting data. The methods of degrading the images used to develop the perception model were mathematically related to methods employed in objective laboratory-scale image quality testing. Thus, the perception model could be used to establish pass/fail criteria for objective laboratory-scale image quality tests of nonuniformity, spatial resolution, and effective temperature range for fire service thermal imagers. The perception model was applied to images that were collected using a high resolution visible camera focused on the thermal imager's display while the thermal imager viewed a variety of thermal targets. In this way, the subjectivity of human perception testing is applied equally to all thermal imagers being tested for compliance to a nationally standardized set of image quality tests. As fire service imaging needs and test methods evolve, the perception testing can be updated with different image types and scenarios.

Night Vision and Electronic Sensors Directorate (NVESD) Modeling and Simulation Division (MSD) sensor models, such as NV Therm IP, are developed through perception experiments that investigate phenomena associated with sensor performance (e.g. sampling, noise, sensitivity). A standardized laboratory perception testing method developed in the mid-1990's has been responsible for advances in sensor modeling that are supported by field sensor performance experiments.1 The number of participants required to yield dependable results for these experiments could not be estimated because the variance in performance due to participant differences was not known. NVESD and George Mason University (GMU) scientists measured the contribution of participant variance within the overall experimental variance for 22 individuals each exposed to 1008 stimuli. Results of the analysis indicate that the total participant contribution to overall experimental variance was between 1% and 2%.

The Night Vision and Electronic Sensors Directorate's current time-limited search model, which makes use of the targeting task performance (TTP) metric to describe imager quality, does not explicitly account for the effects of clutter on observer performance. The masked target transform volume (MTTV) clutter metric has been presented previously, but is first applied to the results of a vehicle search perception experiment with simulated thermal imagery here. NVESD's Electro-Optical Simulator program was used to generate hundreds of synthetic images of tracked vehicles hidden in a rural environment. 12 observers searched for the tracked vehicles and their performance is compared to the MTTV clutter level, signal-to-clutter ratios using several clutter metrics from open literature, and to the product of target size and contrast. The investigated clutter metrics included the Schmeider-Weathersby statistical variance, Silk's statistical variance, Aviram's probability of edge detection metric, and Chang's target structural similarity metric. The MTTV was shown to better model observer performance as measured by the perception experiment than any of the other compared metrics, including the product of target size and contrast.

The standard model used to describe the performance of infrared sensors is the U.S. Army thermal target acquisition model, NVThermIP. The model is characterized by the apparent size and contrast of the target, and the resolution and sensitivity of the sensor. Currently, manual gain and level determine optimal contrast for military targets. The Night Vision models are calibrated to such images using a spatial average contrast consisting of the root sum squared of the difference between the target and background means, and the standard deviation of the target internal contrast. This definition of contrast applied to the model will show an unrealistic increase in performance for saturated targets. This paper presents a modified definition of target contrast for use in NVThermIP, including a threshold value for target to background mean difference and means to remove saturated pixels from the standard deviation of the target. Human perception experiments were performed and the measured results are compared with the predicted performance using the modified target contrast definition in NVThermIP.

How to quantify something that is typically subjective in nature can be a daunting task. Image quality is no exception and the pursuit of quantifiable results has thus led to an exhaustive battery of tests, methodology, and reporting formats. How many specifications are really required of a camera to establish its imaging performance? Of these which are actually pertinent and further which are truly unique? Most all design decisions can eventually be reduced down to a simple tradeoff. Whether it be, for example, weight versus strength or cost versus reliability there is always a struggle to be had at some point during the design process. For sensor makers this tradeoff typically manifests as resolution versus sensitivity. It is irrelevant to have a 100 megapixel sensor if the pixels are not sensitive enough to respond to reasonable illumination. On the other hand it is also irrelevant if you can image with virtually no light but do not have enough pixels to resolve your subject. Resolution and sensitivity are essential to ascertaining imager performance. This paper will discuss how these two specifications are more than just a megapixel count or simply an ISO film speed equivalent. Resolution of a sensor is best reported as its modulation transfer function (MTF) and sensitivity is more informative when described in terms of a photon transfer curve (PTC). This paper will show how to create and interpret these two curves and finally how to translate the results back into the qualitative realm.

This paper details the development, experimentation, collected data and the results of research designed to gain an understanding of the effects of clutter on the temporal and spatial image collection guidelines for tracking urban vehicles. More specifically, a quantitative understanding of the relationship between human observer performance and the spatial and temporal resolution is sought. Performance is measured as a function of the number of video frames per second, imager spatial resolution and the ability of the observer to accurately determine the destination of a moving vehicle target as it encounters vehicles with similar infrared signatures. The research is restricted to data and imagery collected from altitudes typical of modern low to mid altitude persistent surveillance platforms using a wide field of view. The ability of the human observer to perform an unaided track of the vehicle was determined by their completion of carefully designed perception experiments. In these experiments, the observers were presented with simulated imagery from Night Vision's EOSim urban terrain simulator. The details of the simulated targets and backgrounds, the design of the experiments and their associated results are included in this treatment.

The protection of ships against infrared guided missiles is a concern for modern naval forces. The vulnerability of ships can be reduced by applying countermeasures such as infrared decoys and infrared signature reduction. This paper will present a set of simulation tools which can be used for assessing the effectiveness of these measures. The toolset consists of a chain of models which calculate the infrared signature of a ship (EOSM), generate an infrared image of the ship in a realistic sea and sky background (EOSTAR) and determine the behaviour of an infrared missile seeker against these images and simulate the complete missile fly-out including countermeasure deployment (EWM). All model components will be briefly discussed. Typical simulation runs will be shown.

In order to facilitate systematic, computer aided improvements of camouflage and concealment assessment methods, the software system CART (Camouflage Assessment in Real-Time) was built up for the camouflage assessment of objects in multispectral image sequences (see contributions to SPIE 2007, SPIE 2008 and SPIE 2009 [1], [2], [3]). It comprises a semi-automatic marking of target objects (ground truth generation) including their propagation over the image sequence and the evaluation via user-defined feature extractors. The conspicuity of camouflaged objects due to their movement can be assessed with a purpose-built processing method named MTI snail track algorithm. This paper presents the enhancements over the recent year and addresses procedures to assist the camouflage assessment of moving objects for image data material with strong noise or image artefacts. This extends the evaluation methods significantly to a broader application range. For example, some noisy infrared image data material can be evaluated for the first time by applying the presented methods which fathom the correlations between camouflage assessment, MTI (moving target indication) and dedicated noise filtering.

The aim of this paper is to explain how the combination of CFD++, CFD computational code, RadTherm-IR, 3D thermal computational code and SE-Workbench-EO from OKTAL-SE is an adequate solution for computing the IR signature of a jet aircraft taking all this major into account. An F16 fighter jet cruising at Ma=0.8 has been simulated in CFD++ including a multi species gas with the plume included in the CFD simulation. The solution adopted for computing the radiative transfer through the plume is based on the IRMA module of the NIRATAM software package. A revisited and extended version of IRMA has been integrated in the non real time rendering module of the SE Workbench-EO, SE-RAY-IR The paper illustrates the use of SE-RAY-IR for computing the IR signature of the F16, including the plume, either as an isolated target in the sky or with the background behind.

Methods of analysing the signature and susceptibility of naval platforms to infrared detection are described. An unclassified ShipIR destroyer model is used to illustrate the primary sources of infrared signature and detection: the exhaust system, solar-heating, and operating climate. The basic detection algorithm used by the Naval Threat Countermeasure Simulator (NTCS) component of ShipIR is described and used to analyse the effectiveness of various stealth technologies: stack suppression, low solar absorptive (LSA) paints, and Active Hull Cooling (AHC). Standard marine climate statistics are used to determine a minimum (5%), average (50%) and maximum (95%) signature condition for each operating region. The change in detection range of two wave-band sensors (3-5μm, 8-12 μm) operating at different altitudes (10m, 270m) in each of four climatic conditions is used to assess the effectiveness of each stealth solution, providing a more integral approach to infrared stealth design. These tools and methods form the basis on which future platform designs are being evaluated.

Atmospheric turbulence is an imaging phenomenon that introduces blur, distortion, and intensity fluctuations that corrupt image quality and can decrease target acquisition performance. The modeling of imaging sensors requires an accurate description of turbulence effects. We present two novel methodologies for the measurement of the turbulence MTF in infrared imagery. First, the structural similarity metric is used to compare pristine and degraded imagery. Second, contrast modulations of radial bar targets are analyzed to extract an equivalent blur. Human perception tests are compared against model predictions. The results show that complex turbulence effects can be measured and modeled with simple MTF blurs.

To perform radiometric calibrations of image data, reference sources are needed in order to acquire data at two or more radiance levels giving the calibration parameters. Due to sensor drift for detectors in the infrared region the parameters have to be frequently recalculated during an extended signature measurement if the accuracy is to be maintained. In signature measurements where the incident radiance levels from hot targets are exceeding the background by many orders of magnitude the reference sources need to emit radiation at high radiance levels. Such reference sources are more complex and so is the handling of these sources. The calibration procedure tends to become impractical in field trials where several spectral bands are involved, which increases the need for reference data and the number of reference sources. A method to radiometric calibrate hotspot target data by using only a few simple reference sources close to ambient temperatures has been evaluated in this paper. Reference data has been collected both in laboratory studies and in field trials at various weather conditions. The accuracy and the precision of the method are presented. The uncertainty due to sensor drift is estimated. Error sources connected to the calibration method are discussed.

This paper describes a simple but powerful method for calibrating the apparent broadband flux reflectance of target and background materials in short wave infrared (SWIR) imagery in the field, a method that can also be used in other reflective bands. The method is analogous to the approach of field calibration of thermal IR (infrared) imagery in which thermally regulated emissive references are positioned in a peripheral region of the sensor FOV to provide apparent temperature versus image grayscale. The principle difference between the emissive TIR approach and the reflective approach described here is that passive, well calibrated reflective references are used for the SWIR and do not require active emission of in-band radiation. This approach was recently used in a field collection using a high quality, well characterized broadband SWIR imager. Theory, analysis, and results are presented here.

The presence of noise in an IR system adversely impacts task performance in many cases. Typically when modeling the effect of noise on task performance the focus is on the noise generated at the front end of the system (detector, amplifier, etc). However, there are cases when noise may arise in the post-sample of the system due to different display technologies, etc. This paper presents a means to determine the effect of display noise on the sensor system noise under a variety of conditions. A modeling study demonstrates that the effect of display noise correlates to the predicted modeled performance.

Accurate radiometric calibration is a key feature of modern infrared cameras. Considering the newly available infrared focal plane arrays (FPA) exhibiting very high spatial resolution and faster readout speed, we developed a method to provide a dedicated radiometric calibration of every pixel. The novel approach is based on detected fluxes rather than detected counts as is customarily done. This approach features many advantages including the explicit management of the main parameter used to change the gain of the camera, namely the exposure time. The method not only handles the variation of detector spectral responsivity across the FPA pixels but also provides an efficient way to correct for the change of signal offset due to camera self-emission and detector dark current. The method is designed to require as few parameters as possible to enable a real-time implementation for megapixel-FPAs and for data throughputs larger than 100 Mpixels/s. Preliminary results with a high-speed 3 μm to 5 μm infrared camera demonstrate that the method is viable and yields small radiometric errors.

Point Spread Function (PSF), Modulation Transfer Function (MTF) and Ensquared Energy (EE) are important performance indicators of optical systems for surveillance, imaging and target tracking applications. We report on the development of a new measurement method which facilitates fast real time measurement of the two dimensional PSF and related performance parameters of a MWIR optical module under room temperature as well as under extreme temperature conditions. Our new measurement setup uses the law of reversibility of optical paths to capture a highly resolved, magnified image of the PSF. By using of an easy add-on thermally insulating enclosure the optical module can be exposed to and measured under both variable high and low temperatures (-50°C up to 90°C) without any external impact on the measurement. Also line of sight and various off-axis measurements are possible. Common PSF and MTF measurement methods need much more correction algorithms, whilst our method requires mainly a pinhole diameter correction only and allows fast measurements of optical parameters under temperature as well as fast and easy adjustment. Additionally comparison of the captured, highly resolved PSF with optical design data enables purposeful theoretical investigation of occurring optical artifacts.

Electro Optical technology continues to advance, incorporating developments in infrared and laser technology into smaller, more tightly-integrated systems that can see and discriminate military targets at ever-increasing distances. New systems incorporate laser illumination and ranging with gated sensors that allow unparalleled vision at a distance. These new capabilities augment existing all-weather performance in the mid-wave infrared (MWIR) and long-wave infrared (LWIR), as well as low light level visible and near infrared (VNIR), giving the user multiple means of looking at targets of interest. There is a need in the test industry to generate imagery in the relevant spectral bands, and to provide temporal stimulus for testing range-gated systems. Santa Barbara Infrared (SBIR) has developed a new means of combining a uniform infrared source with uniform laser and visible sources for electro-optics (EO) testing. The source has been designed to allow laboratory testing of surveillance systems incorporating an infrared imager and a range-gated camera; and for field testing of emerging multi-spectral/fused sensor systems. A description of the source will be presented along with performance data relating to EO testing, including output in pertinent spectral bands, stability and resolution.

Given the frequent lack of a reference image or ground truth when performance testing Bayer pattern color filter array (CFA) demosaicing algorithms, two new no-reference quality assessment algorithms are proposed. These new quality assessment algorithms give a relative comparison of two demosaicing algorithms by measuring the presence of two common artifacts in their output images. For this purpose, various demosaicing algorithms are reviewed, especially adaptive color plane, gradient based methods, and median filtering, with particular attention paid to the false color and edge blurring artifacts common to all demosaicing algorithms. Classic quality assessment methods which require a reference image, such as MSE, PSNR, and ΔE, are reviewed, their typical usage characterized, and their associated pitfalls identified. With this information in mind, the motivations for no-reference quality assessment are discussed. The new quality assessment algorithms are then designed for a relative comparison of two images demosaiced from the same CFA data by measuring the sharpness of the edges and determining the presence of false colors. Demosaicing algorithms described earlier are evaluated and ranked using these new algorithms. A large quantity of real images is given for review. These images are also used to justify those rankings suggested by the new quality assessment algorithms. This work provides a path forward for future research investigating possible relationships between CFA demosaicing and color image super-resolution.

A flexible tool for collection of data from imaging sensors is presented. It is compatible to Windows XP and later. It is designed to meet demanding requirements in scientific applications and has been evaluated both in laboratory measurements and extended field trials. Main features of the image capturing software, denoted D8, are: D8 supports various kinds of cameras: monospectral, multispectral and hyperspectral. A new camera is included by adding additional information in a configuration list. The image data acquired from D8 are standardized into formats based on the ENVI format. Each single image gets a timestamp with the precision of 1 ms. There is support for an FPGA board, which can improve the precision to 1 μs. Through D8 an arbitrary number of cameras can be temporally synchronized and the data collected. This options imitates true multi-colour cameras. Results from a temporal synchronization and spatial alignment of two multiband cameras are presented.

Besides resolution, an important performance parameter of a FIR camera is the sensitivity. It depends on the sensitivity of the detector array itself and the characteristics of the optic. The effects of the optic are considerably driven by the f-number, with high values resulting in decreased sensitivity, but providing the possibility for simple lens design and cheaper production costs. In this contribution 4 different sensor setups with different optics are evaluated for their impact on the performance of trained pedestrian classifiers. To overcome the expensive and time consuming process of ground truth generation for multiple sensors, an approach for reusing available high sensitivity reference data is presented. Classifiers are trained on specially transformed reference data with characteristics of sensors with degraded sensitivity. For the evaluation of the classifiers, data of real world road scenarios is collected simultaneously with the target sensors mounted in parallel in a test vehicle, following a detailed script for recording a pedestrian scene test catalogue. This allows for a direct analysis and comparison of the different sensors and their impact on the detection performance.

This paper presents a comparison between measurements of the spectral radiant intensity of Magnesium/Teflon®/Viton® (MTV) flares and theoretical estimation using available mathematical models in the range of 0.6 μm up to 11.5 μm. It is used an indigenous system capable of hold the flare pellets in the same position during the burning time and reproduce the airflow after an actual air launching at different velocities. Two mathematical models are studied and adapted to predict MVT flare radiant intensity and average emissivity from visible to long wavelength infrared. The results indicate that the adapted models can be use to estimate the MTV flare parameters in different situations with good accuracy.