Van A. Hodgkin

What good is SWIR? Passive day comparison of VIS, NIR, and SWIR

This paper is the first of three papers associated with the military benefits of SWIR imaging. This paper describes the benefits associated with passive daytime operations with comparisons of SWIR, NIR, and VIS bands and sensors. This paper includes quantitative findings from previously published papers, analysis of open source data, summaries of various expert analyses, and calculations of notional system performance. We did not accept anecdotal findings as acceptable benefits. Topics include haze and fog penetration, atmospheric transmission, cloud and smoke penetration, target and background contrasts, spectral discrimination, turbulence degradation, and long range target identification. The second and third papers will address passive night imaging and active night imaging.

Minimum resolvable temperature difference measurements on undersampled imagers

Minimum Resolvable Temperature Difference (MRTD) is the primary measurement of performance for infrared imaging systems. Where Modulation Transfer Function (MTF) is a measurement of resolution and three-dimensional noise (or noise equivalent temperature difference) is a measurement of sensitivity, MRTD combines both measurements into a test of observer visual acuity through the imager. MRTD has been incorrectly applied to undersampled thermal imagers as a means for assessing the overall performance of the imager. The incorrect application of the MRTD (or just MRT) test to undersampled imagers includes testing to the half-sample (or Nyquist rate) of the sensor and calling the MRT unresolvable beyond this frequency. This approach is known to give poor predictions in overall system performance. Also, measurements at frequencies below the half-sample rate are strongly dependent on the phase between the sampling geometry and the four-bar target. The result is that very little information in the MRT measurement of an undersampled thermal imager is useful. There are a number of alternatives including Dynamic MRT (DMRT), Minimum Temperature Difference Perceived (MTDP), Triangle Orientation Discrimination (TOD), and objective MRT tests. The NVESD approach is to measure the MTF and system noise and to use these measurements in the MRT calculation to give good sensor performance predictions. This paper describes the problems with MRT for undersampled imagers, describes the alternative measurements, and presents the NVESD approach to MRT measurements.

Impact of path radiance on MWIR and LWIR imaging

Atmospheric radiance occurs in both the MWIR and LWIR primarily as a consequence of thermal emission by the gases and aerosols in the atmosphere. If this radiation originates between a scene and a thermal imaging sensor, its called path radiance. In thermal IR imagery, path radiance reduces scene radiation contrast at the entrance pupil. For ground based sensors, this effect would be most significant in search systems with wide fields of view (WFOV) that image a large range depth of field. In WFOV search systems, the sensor display gain and level are typically adjusted to optimize the contrast of targets and backgrounds at the closer ranges. Without compensation in WFOV imagery, high path radiance can mask distant targets in the detection process. However, in narrow fields of view (NFOV), path radiance can have less of an impact since targets and backgrounds will be at about the same range and thus have the same path radiance. As long as the NFOV radiation contrast exceeds the system noise, sensor display gain and level adjustments, or image processing, if available, can be used to boost the contrast at the display. However, there are some imaging conditions that are beyond compensation by display contrast adjustments or image processing. Using MODTRAN, this paper examines the potential impacts of path radiance from the phenomenological point of view on target-tobackground contrast and signatures (&Dgr;T) for dual band thermal imaging systems

Measurement of uncooled thermal imager noise

Uncooled staring thermal imagers have noise characteristics that are different from cooled thermal imagers (photon detector sensors). For uncooled sensors, typical measurements of some noise components can vary as much as 3 to 5 times the original noise value. Additionally, the detector response often drifts to the point that non-uniformity correction is only good for a short time period. Because the noise can vary so dramatically with time, it can prove difficult to measure the noise associated with uncooled systems. However, it is critical that laboratory measurements provide repeatable and reliable measurement of constructed uncooled thermal imagers. In light of the above difficulties, a primary objective of this research has been to develop a satisfactory measurement for the noise of uncooled staring thermal imagers. In this research effort, three-dimensional noise (3D Noise) data vs. time was collected for several uncooled sensors after nonuniformity correction. Digital and analog noise data vs. time were collected nearly simultaneously. Also, multiple 3D Noise vs. time runs were made to allow the examination of variability. Measurement techniques are being developed to provide meaningful and repeatable test procedures to characterize the uncooled systems.

Preliminary measurements of contrast in polarimetric signatures of humans

The reflective bands in modern imaging, i.e., the visible through the short wave infrared (SWIR), have become very attractive for use in both daytime and low light target acquisition and surveillance. In addition, the nature of the target in modern conflict again includes the human body as a principle target. The spectral natures of the reflectivities of humans, their clothing, what they may be carrying, and the environments in which they are immersed, along with the spectral nature and strength of the light sources that illuminate them, have been the essential components of the contrasts in the signatures that are used in models that predict probabilities of target acquisition and discrimination. What has been missing is the impact that polarization in these signatures can have on image contrast. This paper documents a preliminary investigation into the contrast in active and passive polarimetric signatures of humans holding two-handed objects in the SWIR.

Hyperspectral waveband group optimization for time-resolved human sensing

Pulse and respiration rates provide vital information for evaluating the physiological state of an individual during triage. Traditionally, pulse and respiration have been tracked by means of contact sensors. Recent work has shown that visible cameras can passively and remotely obtain pulse signals under controlled environmental conditions [2] [5] [14] [27]. This paper introduces methods for extracting and characterizing pulse and respiration signals from skin reflectivity data captured in peak sensitivity range for silicon detector (400nm-1100nm). Based on the physiological understanding [12] [13] [15] of human skin and reflectivity at various skin depths, we optimize a group of spectral bands to determine pulse and respiration with high Peak Signal-to-Noise Ratio (PSNR) and correlation values [27] [30]. Our preliminary results indicate top six optimal waveband groups in about 100nm - 200nm resolution in each, with rank-ordered peaks at 409nm, 512nm, 584nm, 667nm, 885nm and 772nm. This work, collected under an approved IRB protocol enhances non-contact, remote, passive, and real-time measurement of pulse and respiration for security and medical applications.

Modeling of IR sensor performance in cold weather

Noise in an imaging infrared (IR) sensor is one of the major limitations on its performance. As such, noise estimation is one of the major components of imaging IR sensor performance models and modeling programs. When computing noise, current models assume that the target and background are either at or near a temperature of 300 K. This paper examines how the temperature of the scene impacts the noise in IR sensors and their performance. It exhibits a strategy that can be used to make a 300 K assumption-based model to compute the correct noise. It displays the results of some measurements of signatures of a cold target against a cold background. Range performance of a notional 3rd Gen sensor (midwave IR and long wave IR) is then modeled as a function of scene background temperature.

Uncertainties in the minimum resolvable temperature difference measurement

The Minimum Resolvable Temperature Difference (MRTD or MRT) is the most widely accepted and inclusive figure of merit for describing a thermal imaging systems performance. It is the product of analytic mathematical models and traditional man-in-loop system hardware performance measurements that describe IR systems. MRT is a basis for thermal field performance model predictions and is commonly used in specification of thermal imagers. The MRT test is subjective because it requires human observers to just discern increasingly smaller 4-bar patterns as a function of temperature differences between bars and the background. When performed by trained observers, the MRT test is an accurate measure of sensitivity as a function of spatial resolution. The ability to resolve 4-bar patterns varies between observers. Furthermore, MRT is a psychophysical task, for which biases are unavoidable. In this paper, uncertainties in MRT measurements are reported for individual trained observers and between observers as functions of some biases, such as random and fixed pattern noise. For this paper, virtual MRTs were performed on a new, custom visual acuity test simulator, developed for NVESD, that allows precise control over significant sensor and display parameters, and these results are compared. Through a process of eliminating sources of MRT variability, we have been able to quantify the observer variability.

Comparison of ID performance using real and synthetic imagery

Recent experiments performed at the U.S. Army Night Vision and Electronic Sensors Directorate (NVESD) provide significant insight into the validation of synthetic imagery for use in human perception experiments. This paper documents the procedures and results of target identification (ID) experiments using real and synthetic thermal imagery. Real imagery representing notional first generation and advanced scanning sensor systems was obtained. Parameters derived from the sensor data were used to generate synthetic imagery using the NVESD Paint the Night simulation. Both image sets were then used in a target identification experiment with trained human observers. Perception test results were analyzed and compared with metrics derived from the imagery. Several parameters missing from the original truth data were found to correlate with differences in the perception data. Synthetic data were regenerated using these additional parameters. A subsequent perception experiment confirmed the importance of these parameters, and a good match was obtained between real and synthetic imagery. While the techniques used in this series of experiments do not constitute a definitive method for validating synthetic imagery, they point to some important observations on validation. The main observation is that both target and local background characteristics must be sufficiently specified in the truth data in order to obtain good agreement between synthetic and real data. The paper concludes with suggestions as to the level of detail necessary for truth data when using synthetic imagery in perception experiments.

Modeling laser radar systems in the Night Vision Integrated Performance Model (NV-IPM)

Active imaging systems are currently being developed to increase the target acquisition and identification range performance of electro-optical systems. This paper reports on current efforts to extend the Night Vision Integrated Performance Model (NV-IPM) to include laser radar (LADAR) systems for unresolved targets. Combining this new LADAR modeling capability with existing sensor and environment capabilities already present in NV-IPM will enable modeling and trade studies for military relevant systems.