ENHANCED MILITARY TARGET DISCRIMINATION USING ACTIVE AND PASSIVE POLARIMETRIC IMAGERY

Daniel A. Lavigne1, Mélanie Breton2, Mario Pichette1, Vincent Larochelle1, Jean-Robert Simard1

1Defence Research and Development Canada – Valcartier 2459 Pie-XI Blvd. North, Quebec, Qc, Canada G3J 1X5

Phone: (418) 844-4000 ext. 4157, Fax: (418) 844-4511, Email: daniel.lavigne@drdc-rddc.gc.ca

2AEREX Avionics Inc. 36 du Ruisseau, suite 102, Breakeyville, Qc, Canada G0S 1E2

ABSTRACT

Surveillance operations often make use of electro-optic (EO) imaging systems to detect civilian and military targets. To increase the overall target detection performance, such active/passive EO sensors could exploit the polarization of light as additional information to discriminate man made objects against different backgrounds. The target contrast enhancement obtained by analyzing the polarization of the reflected light from either a direct polarized laser source as encountered in active imagers, or from natural ambient illumination, can be used for such target discrimination scheme. This paper reports results from field experiments exploiting polarization-based imaging sensors to enhance the detection of man made objects. Active and passive polarimetric signatures of objects have been acquired at wavelengths in the near and long-wave infrared bands. Results demonstrate to what extent and under which illumination and environmental conditions the exploitation of active/passive polarimetric images is suitable to enable target discrimination.

Index Terms— Polarimetric imaging, contrast enhancement, target discrimination

1. INTRODUCTION Electro-optic (EO) imaging sensors are commonly used to gather information about a scene, in order to detect different targets for applications like surveillance operations and rescue missions. Active and passive polarimetric imaging devices have the potential to enhance the target detection performance of traditional EO sensors, by exploiting the polarization of light to provide additional information about given targets of interest. Active polarimetric imagers, for instance, proved particularly efficient at night and in degraded weather conditions, building on the well known

property that man made objects depolarize less the incident radiation than natural objects do. However, while the polarization of light has been used and studied in the past for numerous applications, the understanding of the polarization phenomenology taking place with targets used in cluttered backgrounds requires additional experimentations. Specifically, the target contrast enhancement obtained by analyzing the polarization of the reflected light from either a direct polarized laser source as encountered in active imagers, or from natural ambient illumination, needs further investigation. Considering that infrared polarization contrast can still exist even when the temperature difference between the target and its background is negligible, it might be useful to process the state of the polarization of the emitted and collected radiation in the near and long-wave infrared (NIR and LWIR) bands [1]. The contrast associated with man made objects should therefore be enhanced and thus, target discrimination performance increased.

2. POLARIMETRIC IMAGING SENSORS Two polarimetric imaging systems have been used for the experiments: the VIZIR (Visible Infrared) system operating in the near infrared and LWIR (Long Wave InfraRed), a CO2 laser-based system operating in the long-wave infrared spectral band. 2.1 VIZIR imaging sensor The VIZIR imaging sensor is made up of a range-gated intensified CCD camera with a 10X zoom lens, a laser diode array illuminator, and the requisite electronics required for system synchronization and control. The operating wavelength is a laser source at 860 nm and offered the possibility to select its laser divergence between two discrete values of 2-15 degrees, while the camera FOV was

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continuously variable between 4 and 33 degrees. The camera intensifier is a Gen III Omnibus IV tube with a spectral response peaked between 650 and 850 nm. Figure 1 illustrates the VIZIR system combined with the LWIR one.

Figure 1. VIZIR and LWIR imaging sensors (front view)

2.2 LWIR imaging sensor The Long Wave InfraRed (LWIR) system is made up of a bolometer infrared camera and a Synrad CO2 laser illuminator operating in the far-infrared portion of the spectrum at 10.6 μm, with a divergence of 5 degrees while the camera FOV was fixed at 20 degrees. The camera is an uncooled microbolometer E6000 from Nytech with a spectral response between 8 and 12 μm but peaked at 11 μm. A filter peaked at 10.6 μm with a bandwidth of 600 nm can be flipped in the system receiver. Figure 2 shows a close-up view of the LWIR sensor.

Figure 2. LWIR sensor (close-up view)

3. METHODOLOGY

The main objective of the experiments was to acquire polarimetric signatures of a large set of civilian and military targets, using two different imaging systems, and investigate the use of these signatures to discriminate targets against different backgrounds. The target contrast enhancement is obtained by analyzing the polarization of the reflected light from a direct polarized laser source and from natural ambient illumination. For active imagers, the target contrast

enhancement is obtained by illuminating the scene with a polarized laser source and then by analyzing the polarization of the reflected light from the targets. Such active imagers have been efficient at night and in degraded weather conditions. Furthermore, these active devices have demonstrated that range gating provided extent immunity to blooming effects specific to highly sensitive sensors, and eliminate most of the light backscattered by aerosols. During the experiments, images were acquired in winter and summer time, at daytime and nighttime. Targets were static during the measurement sessions and orthogonally polarized images at various ranges were captured for each of them. 3.1 The experiments The foundation of our experiments is based on the hypothesis that the exploitation of the polarization of reflected light from targets of interest has the potential to provide additional information than typical EO sensors, and thus enhance significantly the resulting target detection performance. Indeed, knowing that the incident light from the illuminator will be less depolarized by man made objects than by natural ones, an image encoded by the degree of polarization shall allow the distinction between man made objects and natural background, even in the case of same reflectivity [2].

The image acquisitions were conducted according to two experiments: one held at the Canadian Forces Base Valcartier (Quebec, Canada) and the second held in Baldersheim (France). The first experiment was held during winter time: Data were captured according to scenarios that include vehicles, camouflage textiles (such as nets and clothing), and compacted and disturbed snow. The second experiment was conducted during summer time: Data captured were from measurements on urban environments, civilian and military vehicles, nets and clothing. 3.2 Stokes parameters The representation of the radiation backscattered by the targets – unpolarized, partially polarized, completely polarized, circularly or elliptically polarized – is achieved through the use of the Stokes parameters. The quantification of the polarization can be achieved by the Stoke parameters (I, Q, U, V) to define the degree of polarization:

0222 SAAAI yx (1)

122 SAAQ yx (2)

2cos2 SAAU yx (3)

3sin2 SAAV yx (4)

where Ax, Ay are the amplitudes of the electromagnetic waves in mutually perpendicular directions, A2 is the intensity, is the phase angle between Ax and Ay, < >

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indicates time averaging, and I2 = Q2 + U2 + V2. I is the intensity of radiation and is the result of photometric measurements. Q is the difference between the intensities of radiation in the mutually perpendicular directions used to specify Ax and Ay. U indicates the excess of radiation in the +45o direction over that in the +135o direction relative to the plane of vision. V is the amount of circular polarized radiation. During the experiments, polarimetric data were recorded assuming that the laser light is polarized in order to rotate a linear polarizer, which enable the measurement of the first three Stokes components. 3.3 Orthogonal state contrast image Polarimetric imaging can be used for characterizing material and observing contrast that are not detectable in conventional intensity images. Analyzing the backscattered light in the polarization states parallel and orthogonal to the incident one may reveal important features that may not be discernible in intensity images. It has been reported that such polarimetric images are independent of the spatial non-uniformity of the illumination, since they are normalized by the local total intensity [3]. In order to improve the contrast level of the targets from its background, two images of the scene are acquired, one for each laser-camera polarization configuration. With such configuration, each image is formed from an average of a train of three images acquired successively to reduce the resulting noise.

The first image s1(i,j) corresponds to reflected light with the same polarization state as the incident light: this is obtained by fixing horizontally both the laser polarization and the camera polarizer. The second image s2(i,j) corresponds to the reflected light with orthogonal polarization and is obtained by orienting the polarizer in front of the camera vertically and leaving the laser polarization horizontal. For the LWIR imaging device, the polarization of the laser is horizontally linearly polarized and therefore, only the grid-wire facing the camera is rotated. The difference of these two images provides the orthogonal state contrast image (OSCI) and is the total intensity backscattered by the scene, calculated as follows:

jisjisjisjis

ji,,,,,

21

21 (5)

where (i,j) is the coordinates of a given pixel, such that s1(i,j)[s2(i,j)] is the intensity at pixel (i,j) in s1(s2). The OSCI is invariant to illumination nonhomogeneity as it is normalized by the total intensity s1(i,j) + s2(i,j). The joint observation of both images allows the estimation of how the materials in the scene depolarize the incident light. The degree of polarization can be defined by:

2det41

trP (6)

where is the coherency matrix, and det( ) and tr( ) are respectively the determinant and the trace of . For natural textures, diattenuation and retardance effects are negligible. Since materials correspond to the most common situation in natural outdoor scenes and that they can be considered purely depolarizing and isotropic, the coherency matrix is diagonal and thus, the channel s1 and s2 are considered statistically independent. The OSCI is an estimate of the image degree of linear polarization (DOLP) if the observed material is purely depolarizing, which is a natural assumption for natural materials observed in monostatic configuration [2]. Under these conditions, speckle noise and non uniformity effects of the laser are removed in order to improve the contrast of the target from its background [4]. The DOLP, and thus the OSCI, shall be able to reveal targets against natural backgrounds that do not appear with good contrast in intensity images.

4. RESULTS

Active and passive polarimetric images of civilian and military assets have been produced at wavelengths in the NIR and LWIR bands with the two imaging sensors presented in section 2. 4.1 VIZIR Measurements with the VIZIR imaging system were conducted in both active and passive modes since the polarization filter in front of the sensor could be rotated. Figure 3 shows active polarimetric images of a vehicle acquired after sunset, in winter conditions. Some contrast enhancement was observed with the OSCI image (fig.3c).

(a) (b)

(c)

Figure 3. Active polarimetric images (a) s1, (b) s2, and (c) OSCI of a vehicle acquired at 50 meters with VIZIR.

Figure 4 illustrates active polarimetric images acquired from a site containing natural and disturbed snow. Both the tracks and the edges of disturbed snow are polarized. The laser light is reflected in particular polarization at 860 nm.

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(b)(a)

Figure 4. Active polarim , (b) s2, and (c) OSCI of tr 100 meters

4.2 L

ows passive polarimetric images of a military uired at nighttime. The snow surrounding the

(c)

etric images (a) s1acks and disturbed snow acquired at

with VIZIR.

WIR

Figure 5 shehicle acqv

military vehicles shows a certain degree of polarization. The edges of the mountain at the top of the images also show a higher polarization level than the sky.

(a) (b)

(c)

Figure 5. Passive polarimetric images (a) s1, (b) s2, and (c) OSCI of a vehicle acquired a meters with WIR system.

e and passive f civilian and ilitary assets have been produced in the

asurements with

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ilitary targets discrimination”,

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5. CONCLUSIONS Activ polarimetric signatures o

at wavelengths mNIR and LWIR bands with two imaging sensors. The orthogonal state contrast image has been used as an estimate of the total intensity backscattered by the scene.

Using the VIZIR system in active mode, results have demonstrated that polarization does enhance man made object contrast for some targets of interest. Me

the LWIR system showed that far-infrared active polarimetry does improve the target contrast from various natural backgrounds, although the results were not as conclusive as in the near-infrared band. For some targets, only specific parts of the object will effectively show some contrast enhancement. Also, like in the near-infrared band, some targets maintain the polarization of the incident laser beam. In the case of IR targets, they were effective in the passive mode (being non-emissive) but they exhibit high reflectivity and consequently are very easy to detect with a far-infrared polarimetric active imager.

The experiments conducted showed that passive polarimetric imagery has the capability to discriminate disturbed snow edges in the LWIR band

ast enhancement was observed with the VIZIR 860 nm system for that specific scenario. As for the clothing, they showed a low degree of polarization in passive imagery. Nonetheless, a contrast enhancement was obtained in some active polarimetric images, due essentially to the reflectivity (or low emissivity) of the objects of interest to be detected.

Results have also demonstrated that polarimetric thermal imaging target discrimination capability is strongly dependent on the external conditions (i.e. presence of the

the time of day the measurements were carried out, the general weather conditions, etc.). In addition, active polarimetric images offer a slight advantage compared to classical passive images in the LWIR spectral band in winter conditions.

6. REFERENCES [1

face and buried antiptection and Remediation Technologies for P

Mines and Minelike Targets VI, Vol. 4394, pp.164-175, 2001. [2] S. Breugnot, P. Clémenceau, “Modeling and performances of a polarization active imager at =806 nm”, Optical Engineering, 39,

p.2681-2688, 2000. p [3] D.A. Lavigne, M. Breton, M. Pichette, V. Larochelle, J-R Simard, “Evaluation of active and passive polarimetric electro-

ptic imagery for civilian and moProceedings SPIE Polarization: Measurement, Analysis, and Remote Sensing VIII, Orlando (FL), 2008. [4] P. Réfrégier, F. Goudail, N. Roux, “Estimation of the degree of polarization in active coherent imagery by using representation”, ournal of the Optical Society of AmericaJ

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