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.
KEYWORDS: Computer simulations, Scene based nonuniformity corrections, Cameras, Image registration, Motion estimation, Signal processing, Calibration, Error analysis, Signal to noise ratio, Sensors
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.
KEYWORDS: Polarimetry, Polarization, Spatial frequencies, Cameras, Calibration, Scene based nonuniformity corrections, Nonuniformity corrections, Long wavelength infrared, Algorithm development, Video
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.
For the past several years we have been working on strategies to mitigate the effects of IFOV errors on
LWIR microgrid polarimeters. In this paper we present a detailed, theoretical analysis of the source of
IFOV error in the frequency domain, and show a frequency domain strategy to mitigate those effects.
A recent measurement campaign at Vandenberg Air Force Base, Calif. involved taking simultaneous observations with a VHF radar and high-data-rate (1-micron diameter) platinum wires to sense optical turbulence (from temperature fluctuations). The radar observations produce profiles of the refractive index structure parameter (C2n ), the turbulent kinetic energy (σ2t ), the eddy dissipation rate (ε), the inner scale (lo ), the outer scale (Lo ) of turbulence, and wind speed and direction to an altitude of 20 km AGL. The fine wire measurements were taken from the surface with several sensors mounted on a balloon-ring platform sampling in excess of 3 kHz to balloon burst altitudes (typically above 25 km AGL). The main objectives of this effort are to compare the two measurement techniques and to obtain observations that can address several fundamental turbulence issues of the real turbulent atmosphere related to laser beam propagation. To date, modeling and simulation of laser beam propagation through atmospheric turbulence have relied upon a traditional theoretical basis that assumes the existence of homogeneous, isotropic, stationary, and Kolmogorov turbulence. Results presented from the radar observations include C2n, σ2t, ε, lo, and the standard deviation of vertical velocity (σw). A comparison of the profiles of C2n obtained from the two measurement techniques is shown and discussed. A time series of temperature data obtained from a fine wire probe traversing one radar range gate is presented and discussed. Future measurement and analysis efforts are presented.
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.
Microgrid polarimeters are a type of division of focal plane (DoFP) imaging polarimeter that contains a mosaic
of pixel-wise micropolarizing elements superimposed upon an FPA sensor. Such a device measures a slightly
different polarized state at each pixel. These measurements are combined to estimate the Stokes vector at each
pixel in the image. DoFP devices have the advantage that they can obtain Stokes vector image estimates for
an entire scene from a single frame capture. However, they suffer from the disadvantage that the neighboring
measurements that are used to estimate the Stokes vector images are acquired at differing instantaneous fields of
view (IFOV). This IFOV issue leads to false polarization signatures that significantly degrade the Stokes vector
images. Interpolation and other image processing strategies can be employed to reduce IFOV artifacts; however
these techniques have a limit to the amount of enhancement they can provide on a single microgrid image.
Here we investigate algorithms that use multiple microgrid images that contain frame-to-frame global motion
to further enhance the Stokes vector image estimates. Motion-based imagery provides additional redundancy
that can be exploited to recover information that is "missing" from a single microgrid frame capture. We have
found that IFOV and aliasing artifacts can be defeated entirely when these types of algorithms are applied to the
data prior to Stokes vector estimation. We demonstrate results on real LWIR microgrid data using a particular
resolution enhancement technique from the literature.
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.
Division of focal plane (DoFP) polarimeters are a particular class of imaging device that consists of an array
of micropolarizers integrated upon a focal plane array sensor (FPA). Such devices are also called microgrid
polarimeters and have been studied over the past decade with systems being designed and built in all regions
of the optical spectrum. These systems are advantageous due to their rugged, compact design and ability to
obtain a complete set of polarimetric measurements during a single frame capture. One inherent disadvantage
of DoFP systems is that each pixel of the FPA sensor makes a polarized intensity measurement of a different
scene point. These spatial measurements are then used to estimate the Stokes vectors across the scene. Since
each polarized intensity measurement has a different instantaneous field-of-view (IFOV), artifacts are introduced
that can degrade the quality of estimated polarization imagery. Here we develop and demonstrate a visual
enhancement technique that is able to reduce false polarization caused by IFOV error while preserving true
polarization content within the Stokes parameter images. The technique is straight-forward conceptually and is
computationally efficient. All results are presented using data acquired from an actual LWIR microgrid sensor.
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.
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.
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.
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.
Long-wave infrared (LWIR) imaging is a prominent and useful technique for remote sensing applications. Moreover, polarization imaging has been shown to provide additional information about the imaged scene. However, polarization estimation requires that multiple measurements be made of each observed scene point under optically different conditions. This challenging measurement strategy makes the polarization estimates prone to error. The sources of this error differ depending upon the type of measurement scheme used. In this paper, we examine one particular measurement scheme, namely, a simultaneous multiple-measurement imaging polarimeter (SIP) using a microgrid polarizer array. The imager is composed of a microgrid polarizer masking a LWIR HgCdTe focal plane array (operating at 8.3-9.3 μm), and is able to make simultaneous modulated scene measurements. In this paper we present an analytical model that is used to predict the performance of the system in order to help interpret real results. This model is radiometrically accurate and accounts for the temperature of the camera system optics, spatial nonuniformity and drift, optical resolution and other sources of noise. This model is then used in simulation to validate it against laboratory measurements. The precision and accuracy of the SIP instrument is then studied.
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