We report an in-depth experimental characterization and analysis of an infrared active polarimetric imaging system based on the orthogonality breaking polarization-sensing approach. We first recall the principle of this laser scanning polarimetric imaging technique, based on the illumination of a scene by means of a dual-frequency dual-polarization light source. The experimental design is then described, along with measurements on test scenes with known polarimetric properties used to validate/calibrate the imaging system and to characterize its optical properties (sensitivity and resolution). The noise sources that temporally and spatially affect the quality of the orthogonality breaking data are then investigated. Our results show that the raw temporal signals detected at a given location of the scene are perturbed by Gaussian fluctuations, and the spatial information contained in the images acquired through raster scan of the scene are dominated by speckle noise, which is a common characteristic of active polarimetric imaging systems. Finally, the influence of the source temporal coherence on the images is analyzed experimentally, showing that orthogonality breaking acquisitions can still be performed efficiently with a low-coherence source.
We report the experimental validation of a snapshot computational degree of polarization imaging technique, based on local analysis of the statistics of a single speckle image acquisition. The applicability of this imaging technique is demonstrated on various samples, and it precision is analyzed and compared with theoretical predictions. Then, we theoretically study the ability of this approach to discriminate samples with various depolarization degrees while sharing similar reflectance properties. We quantitatively compare the detection performances of this approach with standard with standard polarization imaging strategies and evaluate the increase in spatial resolution required to share similar detection efficiency.
Polarization resolved second harmonic generation (PSHG) is developed to study, at the microscopic scale, the impact of aging on the structure of type I collagen fibrils in two-dimensional coatings. A ribose-glycated collagen is also used to mimic tissue glycation usually described as an indicator of aging. PSHG images are analyzed using a generic approach of the molecular disorder information in collagen fibrils, revealing significant changes upon aging, with a direct correlation between molecular disorder and fibril diameters.
Active polarimetric imagery is a powerful tool for accessing the information present in a scene. The polarimetric images obtained can indeed reveal polarizing properties of the objects that could not appear using conventional imaging systems.1,2 The degree of polarization is a key quantity to define the way the scene polarizes or depolarizes the light. Its estimation3 from images obtained with illumination by coherent light is perturbed by speckle noise. Using the definition developed by Goodman,4 we propose in this paper to perform both a theoretical and a numerical experimental study on the estimation of the degree of polarization. We first present that one can estimate the degree of polarization with only two intensity measures, whereas four measures are used in classical studies. This method may have interesting practical applications. Indeed, the use of only two images could reduce the costs and could improve the acquisition time. The quantification of the loss of precision in the estimation of the degree of polarization is analyzed when one uses two images instead of four. This analysis is based on statistical studies considering the speckle noise in the data. The precision on the estimation of the degree of polarization is compared using either the electric field (that needs four measurements) or only two intensity measures. The theorical results are validated on simulated polarimetric data considering different situations described by different polarization matrices.
We address the problem of degree of polarization estimation in active polarimetric images acquired with laser illumination. This technique provides two images of the same scene which are perturbed with peckle noise. Because of the presence of non homogeneity in the reflected intensity, it can be preferable to estimate the degree of polarization from the "Orthogonal State Contrast Image". It has also been shown that a simple nonlinear transformation of this image leads to data perturbed with additive symmetrical noise, on which simple and efficient estimation and detection techniques can be applied. We propose in this paper to analyse estimation properties of the degree of polarization in these different imaging configurations by comparing the Cramer-Rao bounds for unbiased estimation. We will deduce from this analysis some useful prescriptions for exploiting polarimetric data from such imaging systems.
We propose regularized versions of Maximum Likelihood algorithms for Poisson process with non-negativity constraint. For such process, the best-known (non- regularized) algorithm is that of Richardson-Lucy, extensively used for astronomical applications. Regularization is necessary to prevent an amplification of the noise during the iterative reconstruction; this can be done either by limiting the iteration number or by introducing a penalty term. In this Communication, we focus our attention on the explicit regularization using Tikhonov (Identity and Laplacian operator) or entropy terms (Kullback-Leibler and Csiszar divergences). The algorithms are established from the Kuhn-Tucker first order optimality conditions for the minimization of the Lagrange function and from the method of successive substitutions. The algorithms may be written in a `product form'. Numerical illustrations are given for simulated images corrupted by photon noise. The effects of the regularization are shown in the Fourier plane. The tests we have made indicate that a noticeable improvement of the results may be obtained for some of these explicitly regularized algorithms. We also show that a comparison with a Wiener filter can give the optimal regularizing conditions (operator and strength).