Division of Focal plane imagers have recently been developed for polarimetric imaging. Those sensors use a grid composed of four different pixels with four different polarizers engraved on them. Four of these different pixels form a superpixel which enables the estimation of the linear Stokes vector with a single acquisition. Those sensors are particularly sensitive to the spatial variations of the scene. Therefore, if such variations are non-negligible compared with the measurement noise, the estimation of the state of polarization is corrupted. We propose a method to map the superpixels in which the estimation can be trusted.
KEYWORDS: Signal to noise ratio, Wave plates, Polarization, Monte Carlo methods, Imaging systems, Polarimetry, Sensors, Calibration, Cameras, Signal processing
Polarimetric imaging can be done with a division of focal plane (DoFP) camera. This type of camera uses a grid of superpixels. Each superpixel consists of four neighbor pixels with four polarizers having different orientations in front of them. Thus, this kind of camera enables to estimate the linear Stokes vector in a single acquisition. Full stokes polarimetric imaging can be realized by adding a retarder in front of the DoFP camera and performing at least two acquisitions with two different values of retarder orientation. The effective retardance of the retarder depends on several parameters such as temperature and wavelength, which are not always controlled when using such a camera on the field. Therefore, this retardance may not be known precisely, and using a retardance value different from the true one will lead to a bias in estimating the Stokes parameter S3, which contains the information about circular polarization. This bias may become greater than the estimation standard deviation due to noise and thus have a significant impact on estimation. We demonstrate that thanks to measurement redundancy, it is possible to calibrate this retardance directly from the measurements, provided that three acquisitions instead of two are performed and the signal to noise ratio is sufficient. This autocalibration totally cancels the bias and yields a Stokes vector estimation variance identical to that obtained with the true value of the retardance. We study the practical conditions under which this method can be applied, perform experimental validation of its performance, and propose a criterion to decide if it can be applied depending on the acquired measurements.
We report on the development and field trials of an active polarimetric imager in the SWIR domain. Polarization states are controlled for both emission and analysis. Based on past experience, we focus on Orthogonal State Contrast (OSC) imaging for which two images with orthogonal polarizations are needed. An important feature of the imager is the use of two InGaAs imaging detectors mounted orthogonally on a polarization beam splitter. This allows the synchronous imaging with the two orthogonal polarizations and the real time acquisition of OSC images at video frame rate without temporal artefacts. The demonstrator has been operated during field trials with static and moving scenes. These trials were mainly aimed at the detection of man-made objects (weapons, vehicles …) in complex scenes at up to a few hundreds of meters. Along with the presentation of some example of results, we discuss different representation modes of the polarimetric information.
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