Guillaume Anna

Fully tunable active polarization imager for contrast enhancement and partial polarimetry

We present the design and the practical implementation of a polarimetric imaging system based on liquid-crystal modulators that allows generation and analysis of any polarization state on the Poincaré sphere. This system is more versatile than standard Mueller imagers that are based on optimized, but limited, sets of illumination and analysis states. Examples of benefits brought by these extra degrees of freedom are illustrated on two different applications: contrast enhancement and extraction of partial polarimetric properties of a scene.

Polarimetric target detection in the presence of spatially fluctuating Mueller matrices

In polarimetric imaging systems, the main source of perturbations may not be detection noise but fluctuations of the Mueller matrices in the scene. In this case, we propose a method for determining the illumination and analysis polarization states that allow reaching the highest target detection performance. We show with simulations and real-world images that, in practical applications, the statistics of Mueller matrix fluctuations have to be taken into account to optimize polarimetric imagery.

Optimal discrimination of multiple regions with an active polarimetric imager

Until now, most studies about polarimetric contrast optimization have focused on the discrimination of two regions (a target and a background). In this paper, we propose a methodology to determine the set of polarimetric measurements that optimize discrimination of an arbitrary number of regions with different polarimetric properties. We show on real world examples that in some situations, a few number of optimized polarimetric measurements can overcome the performance of full Mueller matrix imaging.

Optimal Mueller matrix estimation in the presence of Poisson shot noise.

We address the optimization of Mueller polarimeters in the presence of additive Gaussian noise and signal-dependent shot noise, which are two dominant types of noise in most imaging systems. We propose polarimeter architectures in which the noise variances on each coefficient of the Mueller matrix are equalized and independent of the observed matrices.

On the influence of noise statistics on polarimetric contrast optimization

In active scalar polarimetric imaging systems, the illumination and analysis polarization states are degrees of freedom that can be used to maximize the performance. These optimal states depend on the statistics of the noise that perturbs image acquisition. We investigate the problem of optimization of discrimination ability (contrast) of such imagers in the presence of three different types of noise statistics frequently encountered in optical images (Gaussian, Poisson, and Gamma). To compare these different situations within a common theoretical framework, we use the Bhattacharyya distance and the Fisher ratio as measures of contrast. We show that the optimal states depend on a trade-off between the target/background intensity difference and the average intensity in the acquired image, and that this trade-off depends on the noise statistics. On a few examples, we show that the gain in contrast obtained by implementing the states adapted to the noise statistics actually present in the image can be significant.

Joint contrast optimization and object segmentation in active polarimetric images.

We present a method for automatic target detection based on the iterative interplay between an active polarimetric imager with adaptive capabilities and a snake-based image segmentation algorithm. It successfully addresses the difficult situations where the target and the background differ only by their polarimetric properties. This method illustrates the benefits of integrating digital processing algorithms at the heart of the image acquisition process rather than using them only for postprocessing.

Simplified calibration procedure for Mueller polarimeter in transmission configuration

We address calibration of Mueller polarimeters in transmission configuration and in the presence of noise. By comparing the maximum likelihood (ML) method and the extended eigenvalue calibration method, it is found that the ML method yields higher precision in the presence of noise. Moreover, we show that by employing the ML method together with simple constraints on the calibration matrices, it is possible to perform the calibration without using a retarder, and with only polarizers. This result is of great interest for the calibration of multispectral polarimeters.

On the performance of the physicality-constrained maximum-likelihood estimation of Stokes vector.

We address the estimation of the Stokes vectors taking into account the physical realizability constraint. We propose a fast method for computing the constrained maximum-likelihood (CML) estimator for any measurement matrix, and we compare its performance with the classical empirical physicality-constrained estimator. We show that when the measurement matrix is based on four polarization states spanning a regular tetrahedron on the Poincaré sphere, the two estimators are very similar, but the CML provides a better estimation of the intensity. For an arbitrary measurement matrix, the CML estimator does not always yield better estimation performance than the empirical one: their comparative performances depend on the measurement matrix, the actual Stokes vector and the signal-to-noise ratio.

Maximum likelihood method for calibration of Mueller polarimeters in reflection configuration.

We address calibration of Mueller polarimeters in the presence of noise. We compare an extension of the eigenvalue calibration method (ECM) and a maximum likelihood (ML) method. The performances of these two calibration methods are investigated with numerical simulations and real experiments on a broadband infrared polarimeter. It is found that the ML method is superior to the extended ECM in terms of calibration precision and can be used at lower signal-to-noise ratio.

General state contrast imaging: an optimized polarimetric imaging modality insensitive to spatial intensity fluctuations

In active polarization imaging, one frequently needs to be insensitive to noninformative spatial intensity fluctuations. We investigate a way of solving this issue with general state contrast (GSC) imaging. It consists in acquiring two scalar polarimetric images with optimized illumination and analysis polarization states, then forming a ratio. We propose a method for maximizing the discrimination ability between a target and a background in GSC images by determining the optimal illumination and analysis states. A further advantage of this approach is to provide an objective way of quantifying the performance improvement obtained by increasing the number of degrees of freedom of a GSC imager. The efficiency of this approach is demonstrated on simulated and real-world images.