Wiley T. Black

The effects of thermal equilibrium and contrast in LWIR polarimetric images

Long-wave infrared (LWIR) polarimetric signatures provide the potential for day-night detection and identification of objects in remotely sensed imagery. The source of optical energy in the LWIR is usually due to thermal emission from the object in question, which makes the signature dependent primarily on the target and not on the external environment. In this paper we explore the impact of thermal equilibrium and the temperature of (unseen) background objects on LWIR polarimetric signatures. We demonstrate that an object can completely lose its polarization signature when it is in thermal equilibrium with its optical background, even if it has thermal contrast with the objects that appear behind it in the image.

Unpolarized calibration and nonuniformity correction for long-wave infrared microgrid imaging polarimeters

Recent developments for long-wave infrared (LWIR) imaging polarimeters include incorporating a microgrid polarizer array onto the focal plane array. Inherent advantages over other classes of polarimeters include rugged packaging, inherent alignment of the optomechanical system, and temporal synchronization that facilitates instantaneous acquisition of both thermal and polarimetric information. On the other hand, the pixel-to-pixel instantaneous field-of-view error that is inherent in the microgrid strategy leads to false polarization signatures. Because of this error, residual pixel-to-pixel variations in the gain-corrected responsivity, the noise-equivalent input, and variations in the pixel-to-pixel micropolarizer performance are extremely important. The degree of linear polarization is highly sensitive to these parameters and is consequently used as a metric to explore instrument sensitivities. We explore the unpolarized calibration issues associated with this class of LWIR polarimeters and discuss the resulting false polarization signature for thermally flat test scenes.

Image processing methods to compensate for IFOV errors in microgrid imaging polarimeters

Long-wave infrared imaging Stokes vector polarimeters are used in many remote sensing applications. Imaging polarimeters require that several measurements be made under optically different conditions in order to estimate the polarization signature at a given scene point. This multiple-measurement requirement introduces error in the signature estimates, and the errors differ depending upon the type of measurement scheme used. Here, we investigate a LWIR linear microgrid polarimeter. This type of instrument consists of a mosaic of micropolarizers at different orientations that are masked directly onto a focal plane array sensor. In this scheme, each polarization measurement is acquired spatially and hence each is made at a different point in the scene. This is a significant source of error, as it violates the requirement that each polarization measurement have the same instantaneous field-of-view (IFOV). In this paper, we first study the amount of error introduced by the IFOV handicap in microgrid instruments. We then proceed to investigate means for mitigating the effects of these errors to improve the quality of polarimetric imagery. In particular, we examine different interpolation schemes and gauge their performance. These studies are completed through the use of both real instrumental and modeled data.

Evaluation and display of polarimetric image data using long-wave cooled microgrid focal plane arrays

Recent developments for Long Wave InfraRed (LWIR) imaging polarimeters include incorporating a microgrid polarizer array onto the focal plane array (FPA). Inherent advantages over typical polarimeters include packaging and instantaneous acquisition of thermal and polarimetric information. This allows for real time video of thermal and polarimetric products. The microgrid approach has inherent polarization measurement error due to the spatial sampling of a non-uniform scene, residual pixel to pixel variations in the gain corrected responsivity and in the noise equivalent input (NEI), and variations in the pixel to pixel micro-polarizer performance. The Degree of Linear Polarization (DoLP) is highly sensitive to these parameters and is consequently used as a metric to explore instrument sensitivities. Image processing and fusion techniques are used to take advantage of the inherent thermal and polarimetric sensing capability of this FPA, providing additional scene information in real time. Optimal operating conditions are employed to improve FPA uniformity and sensitivity. Data from two DRS Infrared Technologies, L.P. (DRS) microgrid polarizer HgCdTe FPAs are presented. One FPA resides in a liquid nitrogen (LN2) pour filled dewar with a 80°K nominal operating temperature. The other FPA resides in a cryogenic (cryo) dewar with a 60° K nominal operating temperature.

Mitigation of image artifacts in LWIR microgrid polarimeter images

Microgrid polarimeters, also known as division of focal plane (DoFP) polarimeters, are composed of an integrated array of micropolarizing elements that immediately precedes the FPA. The result of the DoFP device is that neighboring pixels sense different polarization states. The measurements made at each pixel can be combined to estimate the Stokes vector at every reconstruction point in a scene. DoFP devices have the advantage that they are mechanically rugged and inherently optically aligned. However, they suffer from the severe disadvantage that the neighboring pixels that make up the Stokes vector estimates have different instantaneous fields of view (IFOV). This IFOV error leads to spatial differencing that causes false polarization signatures, especially in regions of the image where the scene changes rapidly in space. Furthermore, when the polarimeter is operating in the LWIR, the FPA has inherent response problems such as nonuniformity and dead pixels that make the false polarization problem that much worse. In this paper, we present methods that use spatial information from the scene to mitigate two of the biggest problems that confront DoFP devices. The first is a polarimetric dead pixel replacement (DPR) scheme, and the second is a reconstruction method that chooses the most appropriate polarimetric interpolation scheme for each particular pixel in the image based on the scene properties. We have found that these two methods can greatly improve both the visual appearance of polarization products as well as the accuracy of the polarization estimates, and can be implemented with minimal computational cost.

The balloon ring: a high-performance low-cost instrumentation platform for measuring atmospheric turbulence profiles

Balloons, similar to those used for meteorological observations, are commonly used to carry a small instrumentation package for measuring optical turbulence in the atmosphere as a function of altitude. Two temperature sensors, one meter apart, measure a single point of the temperature structure function. The raw data is processed to provided the value of CT2, and the results transmitted to a ground receiving site. These data are converted to the index of refraction structure constant, Cn2. The validity of these measurements depend on the correctness of a number of assumptions. These include local isotropy of the turbulence and the existence of the Kolmogorov inertial subrange, and that the data is not contaminated by the wake of the ascending balloon. A variety of experiments on other platforms, and in the laboratory, demonstrate that the assumptions upon which these balloon measurements are made are not valid for a large percentage of the above described flights. In order to collect data whose interpretation did not require preconceived assumptions, the balloon ring instrumentation system was developed. The ring is 8.69 meters in diameter, with a cross-sectional diameter of 14 cm. The ring is hung just below the balloon, so that the wake goes through the center of the ring, and the sensors are mounted tangent to the circumference of the ring. The raw data is transmitted to the ground with a bandwidth extending to 1.25 kHz. A sample of the measurements taken during a flight at Vandenberg Air Force Base, Calif. is presented.

Feedback-integrated scene cancellation scene-based nonuniformity correction algorithm

Abstract. A new registration-based scene-based nonuniformity correction (SBNUC) technique called the feedback-integrated scene cancellation (FiSC) method is introduced, which demonstrates an ability to correct both high- and low-spatial frequency nonuniformity (NU) in infrared focal plane arrays. The theory of scene-cancellation is further developed to include a referencing mechanism that allows spatially correlated NU to be corrected, and a practical method of application is developed. The algorithm is suitable for implementation in a real-time processing environment such as a digital signal processor. A new metric called normalized root mean-squared error for quantifying SBNUC performance is introduced and applied. When applied to real data from a cooled HgTeCd focal plane, the FiSC algorithm outperforms other SBNUC algorithms considered when provided with accurate frame-to-frame image registration. An SBNUC simulation is described and applied to several SBNUC algorithms. When the most realistic case including both high- and low-spatial frequency NU is simulated, the FiSC algorithm outperforms all others tested.

Frequency-domain scene-based non-uniformity correction and application to microgrid polarimeters

Non-uniformity noise is common in infrared imagers, and is usually corrected through calibration, often by momentarily blocking the optical system with a relatively uniform temperature plate. The non-uniformity patterns also tend to drift and require periodic recalibration, necessitating occasional loss of video from the imager during the recalibration process. Microgrid polarimeters are especially sensitive to fixed-pattern noise because the polarization signal is acquired by differentiation of neighboring pixels. Scene-based algorithms attempt to alleviate the need for recalibration of the imager through image processing techniques. We introduce a new frequency-domain scene-based non-uniformity estimation and correction technique, and apply the technique to infrared and microgrid polarimeter imagery. The technique demonstrates promising results for shutter-assisted (recalibration) video, for microgrid polarization systems as well as most spatially modulated sensor systems.

Improving feedback-integrated scene cancellation nonuniformity correction through optimal selection of available camera motion

Abstract. Scene-based nonuniformity correction (SBNUC) techniques provide a means of identifying and correcting focal plane array nonuniformity (NU) through algorithmic analysis of the camera output. SBNUC techniques rely almost universally on camera motion to provide a means of separating the scene from the NU pattern. A simulation is developed that is used to explore the role and effect of camera motion on two representative registration-based SBNUC algorithms: interframe registration-based least mean square (IRLMS) by Zuo et al. and feedback-integrated scene-cancellation (FiSC) by Black and Tyo. The effect of camera motion velocity and direction between frames is examined. The high spatial frequency portion of NU is shown to be corrected by both IRLMS and FiSC, and this correction is relatively indifferent to nonzero camera motion parameters. The FiSC algorithm was specifically designed to incorporate the low spatial frequency component into registration-based SBNUC, but demonstrates a strong dependency on camera motion. Techniques for mitigation of camera motion parameter effects through tradespace and buffering are presented and tested. With proper mitigation and camera motion, FiSC is shown to correct most high and low spatial frequency NU with fewer than 100 framepairs repeatedly processed using techniques suitable for real-time processing implementation.

Combatting infrared focal plane array nonuniformity noise in imaging polarimeters

One of the most significant challenges in performing infrared (IR) polarimetery is the focal plane array (FPA) nonuniformity (NU) noise that is inherent in virtually all IR photodetector technologies that operate in the midwave IR (MWIR) or long-wave IR (LWIR). NU noise results from pixel-to-pixel variations in the repsonsivity of the photodetectors. This problem is especially severy in the microengineered IR FPA materials like HgCdTe and InSb, as well as in uncooled IR microbolometer sensors. Such problems are largely absent from Si based visible spectrum FPAs. The pixel response is usually a variable nonlinear response function, and even when the response is linearized over some range of temperatures, the gain and offset of the resulting response is usually highly variable. NU noise is normally corrected by applying a linear calibration to the data, but the resulting imagery still retains residual nonuniformity due to the nonlinearity of the photodetector responses. This residual nonuniformity is particularly troublesome for polarimeters because of the addition and subtraction operations that must be performed on the images in order to construct the Stokes parameters or other polarization products. In this paper we explore the impact of NU noise on full stokes and linear-polarization-only IR polarimeters. We compare the performance of division of time, division of amplitude, and division of array polarimeters in the presence of both NU and temporal noise, and assess the ability of calibration-based NU correction schemes to clean up the data.