Keith Krapels

Atmospheric turbulence modulation transfer function for infrared target acquisition modeling

A new direction for the US Army Night Vision and Electronic Sensors Directorate is the development of ultra-narrow field of view (UNFOV) infrared target acquisition (TA) systems. Frequently, the per- formance of these systems is limited by atmospheric turbulence in the imaging path. It is desirable to include the effects of atmospheric turbu- lence blur in infrared TA models. The current TA models are currently linear shift invariant (LSI) systems with component modulation transfer functions (MTFs). The use of additional MTFs, to account for atmo- spheric turbulence, requires that the turbulence blur have LSI properties. The primary unresolved issue with the treatment of turbulence blur as an MTF is the LSI characteristics of the blur. Significant variation in spatial blur and temporal blur prohibit the use of a single MTF in an LSI target acquisition model. Researchers at Ben-Gurion University (BGU) use a TA model that includes an LSI blur, which is a temporal average of the turbulence blur. The research described here evaluates the BGU-type treatment of atmospheric MTF and determines it reasonable for inclusion in the US Armys TA model. In addition to the spatial characteristics, the temporal variation of the turbulence blur is also described.

Characteristics of infrared imaging systems that benefit from superresolution reconstruction

There have been numerous applications of superresolution reconstruction algorithms to improve the range performance of infrared imagers. These studies show there can be a dramatic improvement in range performance when superresolution algorithms are applied to undersampled imager outputs. These occur when the imager is moving relative to the target, which creates different spatial samplings of the field of view for each frame. The degree of performance benefit is dependent on the relative sizes of the detector/spacing and the optical blur spot in focal plane space. The minimum blur spot size achievable on the focal plane is dependent on the system F/number. Hence, we provide a range of these sensor characteristics, for which there is a benefit from superresolution reconstruction algorithms. Additionally, we quantify the potential performance improvements associated with these algorithms. We also provide three infrared sensor examples to show the range of improvements associated with provided guidelines.

Current Infrared Target Acquisition Approach for Military Sensor Design and Wargaming

The U.S. Armys infrared target acquisition models have been used for many years by the military sensor community, and there have been significant improvements to these models over the past few years. Significant improvements are the Target Task Performance (TTP) metric for all imaging sensors, the ACQUIRE-LC approach for low contrast infrared targets, and the development of discrimination criteria for the urban environment. This paper is intended to provide an overview of the current infrared target acquisition modeling approach. This paper will discuss recent advances and changes to the models and methodologies used to: (1) design and compare sensors, (2) predict expected target acquisition performance in the field, (3) predict target detection performance for combat simulations, (4) measure and characterize human operator performance in an operational environment (field performance), and (5) relate the models to target acquisition tasks and address targets that are relevant to urban operations. Finally, we present a catalog of discrimination criteria, characteristic dimensions, and target contrasts.

Superresolution performance for undersampled imagers

Enhancement of undersampled imager performance has been demonstrated using superresolution techniques. In these techniques, the optical flow of the scene or the relative subpixel shifts among various snapshots of the scene are calculated, and a high-resolution grid is populated with spatial data using various algorithms. Performance enhancement has been demonstrated for the case of a static image with the undersampled imager compared with a static image that has been acquired through a frame series in a dynamic scene. In this research, the performance is compared for four cases: static image with undersampled imager, static image with superresolution frame sequence, dynamic image with undersampled imager, and dynamic image with superresolution frame sequence.

Target identification performance as a function of temporal and fixed pattern noise

With the increased interest and use of staring IR focal plane arrays, the characterization of fixed pattern noise in task performance is becoming more important. Past work includes theoretical treatments and laboratory measurements to describe the characteristics of fixed pattern noise on target acquisition performance. This is the first target acquisition experiment that describes the relative effects of fixed pattern noise and temporal noise on target identification. Static IR tank images are processed with six different levels of fixed pattern noise and six different levels of temporal noise. A perception experiment is performed where 10 U.S. Army soldiers were tasked to identify the tanks through the combinations of noise. Additive noise was applied in both Gaussian and uniform distributions. The results enable a direct comparison between the effects of fixed pattern noise and temporal noise on target identification.

Probability of identification of small hand-held objects for electro-optic forward-looking infrared systems

This paper describes research on the measurement of the 50% probability of identification cycle criteria (N50,V50) for a set of hand-held objects normally held or used in a single hand. These cycle criteria are used to calibrate the Night Vision Electronic Sensors Directorate (NVESD) target acquisition models. The target set consists of 12 objects, from innocuous to potentially lethal. Objects are imaged in the visible, midwave infrared (MWIR), and long-wave infrared (LWIR) spectrum at 12 different aspects. Two human perception experiments are performed. The first experiment simulates an incremental constriction of the imaging systems modulation transfer function (MTF). The N50, and V50 calibration criteria are measured from this perception experiment. The second experiment not only simulates an incremental constriction of the system MTF but also down samples the imagery to simulate the objects at various ranges. The N50 and V50 values are used in NVTherm 2002 and NVThermIP, respectively, to generate range prediction curves for both the LWIR and MWIR sensors. The range predictions from both NVTherm versions are then compared with the observer results from the second perception experiment. The comparison between the results of the second experiment and the model predictions provides a verification of measured cycle criteria.

Super-resolution for flash ladar imagery.

Flash ladar systems are compact devices with high frame rates that hold promise for robotics applications, but these devices suffer from poor spatial resolution. This work develops a wavelet preprocessing stage to enhance registration of multiple frames and applies super-resolution to improve the resolution of flash ladar range imagery. The triangle orientation discrimination methodology was used for a subjective evaluation of the effectiveness of super-resolution for flash ladar. Results show statistically significant increases in the probability of target discrimination at all target ranges, as well as a reduction in subject response times for super-resolved imagery.

Wide-FOV FPAs for a shipboard distributed aperture system

The Navy faces an ever evolving threat scenario, ranging from sub-sonic sea skimming cruise missiles to newer, unconventional threats such as that experienced by the USS Cole. Next generation naval technology development programs are developing “stealthy” ships by reducing a ships radar cross section and controlling electromagnetic emissions. To meet these threat challenges in an evolving platform environment, ONR has initiated the “Wide Aspect MWIR Array” program. In support of this program, Raytheon Vision Systems (RVS) is developing a 2560 X 512 element focal plane array, utilizing Molecular Beam Epitaxially grown HgCdTe on silicon detector technology. RVS will package this array in a sealed Dewar with a long-life cryogenic cooler, electronics, on-gimbal power conditioning and a thermal reference source. The resulting sub system will be a component in a multi camera distributed aperture situation awareness sensor, which will provide continuous surveillance of the horizon. We will report on the utilization of MWIR Molecular Beam Epitaxial HgCdTe on Silicon material for fabrication of the detector arrays. Detector arrays fabricated on HgCdTe/Si have no thermal expansion mismatch relative to the readout integrated circuits. Therefore large-area focal plane arrays (FPAs) can be developed without concern for thermal cycle reliability. In addition these devices do not require thinning or reticulation like InSb FPAs to yield the high levels of Modulation Transfer Function (MTF) required by a missile warning sensor. HgCdTe/Si wafers can be scaled up to much larger sizes than the HgCdTe/CdZnTe wafers. Four-inch-diameter HgCdTe/Si wafers are currently being produced and are significantly larger than the standard 1.7 inch x 2.6 inch HgCdTe/CdTe wafers. The use of Si substrates also enables the use of automated semiconductor fabrication equipment.

Atmospheric modulation transfer function in the infrared

In high-resolution ultranarrow field-of-view thermal imagers, image quality over relatively long path lengths is typically limited by atmospheric degradation, especially atmospheric blur. We report our results and analyses of infrared images from two sites, Fort A. P. Hill and Aberdeen Proving Ground. The images are influenced by the various atmospheric phenomena: scattering, absorption, and turbulence. A series of experiments with high-resolution equipment in both the 3-5- and 8-13-microm regions at the two locations indicate that, as in the visible, image quality is limited much more by atmosphere than by the instrumentation for ranges even of the order of only a few kilometers. For paths close to the ground, turbulence is more dominant, whereas for paths involving higher average elevation, aerosol modulation transfer function (MTF) is dominant. As wavelength increases, turbulence MTF also increases, thus permitting aerosol MTF to become more dominant. A critical role in aerosol MTF in the thermal infrared is attributed to absorption, which noticeably decreases atmospheric transmission much more than in the visible, thereby reducing high-spatial-frequency aerosol MTF. These measurements indicate that atmospheric MTF should be a basic component in imaging system design and analysis even in the infrared, especially as higher-resolution hardware becomes available.

Target-acquisition performance in undersampled infrared imagers: static imagery to motion video

In this research we show that the target-acquisition performance of an undersampled imager improves with sensor or target motion. We provide an experiment designed to evaluate the improvement in observer performance as a function of target motion rate in the video. We created the target motion by mounting a thermal imager on a precision two-axis gimbal and varying the sensor motion rate from 0.25 to 1 instantaneous field of view per frame. A midwave thermal imager was used to permit short integration times and remove the effects of motion blur. It is shown that the human visual system performs a superresolution reconstruction that mitigates some aliasing and provides a higher (than static imagery) effective resolution. This process appears to be relatively independent of motion velocity. The results suggest that the benefits of superresolution reconstruction techniques as applied to imaging systems with motion may be limited.