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.

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.

Optimization of the contrast in polarimetric scalar images.

We consider active polarimetric imaging systems that illuminate a scene with an incident polarization state and project the backscattered light on another polarization state in order to produce a scalar intensity image. We present and analyze a method for determining the configuration of illumination and analysis polarization states that maximizes the observed contrast between a target and the background when the scene is partially depolarizing and in the presence of additive Gaussian detection noise.

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.

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.

Minimization of the influence of passive-light contribution in active imaging of the degree of polarization.

Active imaging systems that measure the degree of polarization (DOP) are often perturbed by passive light owing to ambient illumination. Passive light introduces a shot noise that combines with the noise due to the active signal to perturb estimation of the DOP. We quantitatively study its influence and show that the polarization state of active illumination can be adjusted to minimize the influence of passive light. It is thus an additional degree of freedom for optimization.

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.