Arnaud Bénière

Near-infrared active polarimetric and multispectral laboratory demonstrator for target detection

We report on the design and exploitation of a real-field laboratory demonstrator combining active polarimetric and multispectral functions. Its building blocks, including a multiwavelength pulsed optical parametric oscillator at the emission side and a hyperspectral imager with polarimetric capability at the reception side, are described. The results obtained with this demonstrator are illustrated on some examples and discussed. In particular it is found that good detection performances rely on joint use of intensity and polarimetric images, with these images exhibiting complementary signatures in most cases.

Estimation precision of the degree of linear polarization and of the angle of polarization in the presence of different sources of noise

We consider imaging systems that measure the three first elements of the Stokes vector and deduce from them the degree of linear polarization and the angle of polarization. They require the acquisition of at least three intensity measurements, but performing more measurements is often thought to improve the estimation precision. We show that if the total acquisition time is fixed, the optimal number of measurements depends on the type of noise that affects the image: the estimation variance increases with the number of measurements N when the noise is additive; it is independent of N in the presence of Poisson shot noise and decreases with N when the angles of the analyzers fluctuate. In general, the optimal number of measurements results from a compromise on the robustness of these different types of perturbations.

Design and experimental validation of a snapshot polarization contrast imager

We present a degree of polarization imaging system based on a Wollaston prism and a single CCD camera. This architecture eliminates technical inaccuracies and noise sources that are present in experimental setups containing a polarization switching element. After the acquisition of two images corresponding to two orthogonal states of polarization, one can compute the orthogonal state contrast image (OSCI), which is an estimate of the local degree of polarization of the backscattered light when the observed materials are purely depolarizing. The instrument design coupled to an efficient calibration enables the estimation of the OSCI from a single image acquisition and significant reduction of technical noise present in other polarization imaging systems. The setup was tested in realistic conditions where it represents a real asset.

Degree of polarization estimation in the presence of nonuniform illumination and additive Gaussian noise

Within the general framework of active imaging we address the degree of polarization (DOP) estimation in the presence of additive Gaussian detector noise. We first study the performance of standard DOP estimators and propose a method to increase estimation precision using physically relevant a priori information. We then consider the realistic case of nonuniform illumination distribution. We derive the Cramer-Rao lower bound and determine a profile likelihood-based estimator. We demonstrate the efficiency of this new estimator and compare its performance with other standard estimators as a function of the degree of nonuniformity of the illumination.

Snapshot active polarimetric and multispectral laboratory demonstrator

In this article we address the design and exploitation of a real field laboratory demonstrator combining active polarimetric and multispectral modes in a single acquisition. Its buildings blocks, including a multi-wavelength pulsed optical parametric oscillator at emission side, and a hyperspectral imager with polarimetric capability at reception side, are described. The results obtained with this demonstrator are illustrated on some examples and discussed.

Sources of possible artefacts in the contrast evaluation for the backscattering polarimetric images of different targets in turbid medium

It is known that polarization-sensitive backscattering images of different objects in turbid media may show better contrasts than usual intensity images. Polarimetric image contrast depends on both target and background polarization properties and typically involves averaging over groups of pixels, corresponding to given areas of the image. By means of numerical modelling we show that the experimental arrangement, namely, the shape of turbid medium container, the optical properties of the container walls, the relative positioning of the absorbing, scattering and reflecting targets with respect to each other and to the container walls, as well as the choice of the image areas for the contrast calculations, can strongly affect the final results for both linearly and circularly polarized light.

Target detection in active polarization images perturbed with additive noise and illumination nonuniformity

Active imaging systems that illuminate a scene with polarized light and acquire two images in two orthogonal polarizations yield information about the intensity contrast and the orthogonal state contrast (OSC) in the scene. Both contrasts are relevant for target detection. However, in real systems, the illumination is often spatially or temporally nonuniform. This creates artificial intensity contrasts that can lead to false alarms. We derive generalized likelihood ratio test (GLRT) detectors, for which intensity information is taken into account or not and determine the relevant expressions of the contrast in these two situations. These results are used to determine in which cases considering intensity information in addition to polarimetric information is relevant or not.

Contrast evaluation of the polarimetric images of different targets in turbid medium: possible sources of systematic errors

Subsurface polarimetric (differential polarization, degree of polarization or Mueller matrix) imaging of various targets in turbid media shows image contrast enhancement compared with total intensity measurements. The image contrast depends on the target immersion depth and on both target and background medium optical properties, such as scattering coefficient, absorption coefficient and anisotropy. The differential polarization image contrast is usually not the same for circularly and linearly polarized light. With linearly and circularly polarized light we acquired the orthogonal state contrast (OSC) images of reflecting, scattering and absorbing targets. The targets were positioned at various depths within the container filled with polystyrene particle suspension in water. We also performed numerical Monte Carlo modelling of backscattering Mueller matrix images of the experimental set-up. Quite often the dimensions of container, its shape and optical properties of container walls are not reported for similar experiments and numerical simulations. However, we found, that depending on the photon transport mean free path in the scattering medium, the above mentioned parameters, as well as multiple target design could all be sources of significant systematic errors in the evaluation of polarimetric image contrast. Thus, proper design of experiment geometry is of prime importance in order to remove the sources of possible artefacts in the image contrast evaluation and to make a correct choice between linear and circular polarization of the light for better target detection.

Detection in polarimetric images in the presence of additive noise and non-uniform illumination

Active polarimetric imaging systems yield information about the intensity contrast and the Orthogonal State Contrast (OSC) in the scene. However, in real systems, the illumination is often spatially or temporally non uniform which creates artificial intensity contrasts that can lead to false alarms. We derive the Generalized Likelihood Ratio Test (GLRT) detectors when intensity information is taken into account or not. These results are used to determine in which cases considering intensity information in addition to polarimetric information is relevant or not.

Estimation and detection in degree of polarization images perturbed by detector noise and non uniform illumination

Active imaging systems that illuminate the scene with polarized light and acquire two images in two orthogonal polarizations yield information about the intensity contrast and the Orthogonal State Contrast (OSC) in the scene. However, in real systems, the illumination is often spatially or temporally non uniform. We first study the influence of this non uniformity on estimation performances. We derive the Cramer Rao Lower Bound and determine a profile likelihood-based estimator. We demonstrate the efficiency of this estimator and compare its performance with other standard estimators as a function of the degree of non-uniformity of the illumination. Concerning target detection, illumination non uniformity creates artificial intensity contrasts that can lead to false alarms. We derive the Generalized Likelihood Ratio Test (GLRT) detectors when intensity information is taken into account or not, and determine the relevant expressions of the contrast in these two situations. These results are used to determine in which cases taking intensity information in addition to polarimetric information is relevant or not.