Depolarization Metrics Research Articles

Mueller-Polarimetry of Barley Leaves I: Depolarization Metrics

In this paper, Mueller polarimetry is applied to study the three groups of common barley leaf samples (Hordeum vulgare) in the visible spectrum (λ = 632.8 nm): Chlorina mutant, Chlorina etiolated mutant and Cesaer varieties. These samples differed in internal leaf structure from genetic mutation or by illumination during growth. Our main concern is to discriminate and characterize these three groups of leaf samples by depolarization metrics: degree of polarization (DoP), average degree of polarization (Average DoP), depolarization index (DI(M)), and Q(M) and R(M) metrics. The results obtained show that all depolarization metrics are sensitive to the sample’s polarization properties. The most effective observable is the Q(M) metric in both forward and backward scattering. The DoP metric showed presence of depolarization anisotropy, which is significantly different for forward and backward scattering for all three groups of samples. Dichroism is observed for both forward and backward scattering, with lower dichroism in forward scattering.

Depolarizing metrics in the biomedical field: Vision enhancement and classification of biological tissues

Polarimetry encompasses a collection of optical techniques broadly used in a variety of fields. Nowadays, such techniques have provided their suitability in the biomedical field through the study of the polarimetric response of biological samples (retardance, dichroism and depolarization) by measuring certain polarimetric observables. One of these features, depolarization, is mainly produced by scattering on samples, which is a predominant effect in turbid media as biological tissues. In turn, retardance and dichroic effects are produced by tissue anisotropies and can lead to depolarization too. Since depolarization is a predominant effect in tissue samples, we focus on studying different depolarization metrics for biomedical applications. We report the suitability of a set of depolarizing observables, the indices of polarimetric purity (IPPs), for biological tissue inspection. We review some results where we demonstrate that IPPs lead to better performance than the depolarization index, which is a well-established and commonly used depolarization observable in the literature. We also provide how IPPs are able to significantly enhance contrast between different tissue structures and even to reveal structures hidden by using standard intensity images. Finally, we also explore the classificatory potential of IPPs and other depolarizing observables for the discrimination of different tissues obtained from ex vivo chicken samples (muscle, tendon, myotendinous junction and bone), reaching accurate models for tissue classification.

Are Indices of Polarimetric Purity Excellent Metrics for Object Identification in Scattering Media?

Polarization characteristics are significantly crucial for tasks in various fields, including the remote sensing of oceans and atmosphere, as well as the polarization LIDAR and polarimetric imaging in scattering media. Many polarimetric metrics (such as the degree of polarization, polarization angle diattenuation, and depolarization) have been proposed to enrich the characterization and improve the task performance in scattering media; yet, their related efficacy is limited, especially in high turbidity conditions. The indices of polarimetric purity (IPPs), including three different depolarization metrics, have been successfully applied to biomedical diagnosis. However, it is still debatable whether IPPs also are excellent metrics for identifying or distinguishing objects in scattering media. In this work, we seek to provide physical insights into the application of distinguishing and identifying different objects via IPPs. Imaging experiments are devised and performed on different objects, e.g., metals and plastics, under different turbidity levels, demonstrating the superiority of IPPs as excellent metrics for object identification in scattering conditions. The experimental results show that the IPPs images can enhance image contrast and improve discriminability, as well as break the limitation of traditional intensity-model imaging techniques when further combined with dehazing or enhancing algorithms. Importantly, as the used Mueller matrix (MM) and the related IPPs can also be obtained via other types of MM polarimeters (e.g., PolSAR and MM microscopy), the proposed solution and idea have potential for such applications as biomedical imaging, photogrammetry, and remote sensing.

Polarization and depolarization metrics as optical markers in support to histopathology of ex vivo colon tissue.

Tissue polarimetry holds great promise to improve the effectiveness of conventional cancer diagnostics and staging, being a fast, minimally invasive, and low-cost optical technique. We introduce an enhanced diagnostic method for ex vivo colon specimens assessment by utilizing Stokes and Mueller matrix polarimetry. The proposed method makes use of experimental Mueller matrices, measured from healthy and tumor zones of a colon specimen, as input data for post-processing algorithms that include physical realisability filtering, symmetric decomposition and estimation of various polarization and depolarization metrics for colon specimen diagnostics. We validated our results with the gold standard histological diagnostics provided by pathologists. It was found that the Stokes-Mueller matrix polarimetry, combined with the appropriate filtering, decomposition algorithms and polarization/depolarization metrics calculations provides relevant optical markers of the colon tissue pathological conditions (healthy versus cancer), as confirmed by histopathology analysis. This approach potentially provides physicians with valuable and complementary information that holds promises in helping with the diagnostics of colon tissue specimens.

Mueller-polarimetry of soil and vegetation in the visible I: Depolarization metrics

In this paper the Mueller polarimetry is applied to study the four natural samples in visible (λ = 632.8 nm): soil, sand, clay and moss. To quantify separability of these samples based on their Mueller matrices we analyze their experimental Mueller matrices by calculating a number of single value depolarization metrics (degree of polarization, average degree of polarization, depolarization index, Q(M)-metric) for each sample in in-plane and out-of-plane geometry of experiment. The results obtained show that all depolarization metrics are sensitive to the sample's polarization properties. The most effective identifier is Q(M)-metric in both experimental geometry.

Melanin concentration and depolarization metrics measurement by polarization-sensitive optical coherence tomography

Imaging of melanin in the eye is important as the melanin is structurally associated with some ocular diseases, such as age-related macular degeneration. Although optical coherence tomography (OCT) cannot distinguish tissues containing the melanin from other tissues intrinsically, polarization-sensitive OCT (PS-OCT) can detect the melanin through spatial depolarization of the backscattered light from the melanin granules. Entropy is one of the depolarization metrics that can be used to detect malanin granules in PS-OCT and valuable quantitative information on ocular tissue abnormalities can be retrived by correlating entropy with the melanin concentration. In this study, we investigate a relationship between the melanin concentration and some depolarization metrics including the entropy, and show that the entropy is linearly proportional to the melanin concentration in double logarithmic scale when noise bias is corrected for the entropy. In addition, we also confirm that the entropy does not depend on the incident state of polarization using the experimental data, which is one of important attributes that depolarization metrics should have. The dependence on the incident state of polarization is also analyzed for other depolarization metrics.

Depolarization metric spaces for biological tissues classification

Classification of tissues is an important problem in biomedicine. An efficient tissue classification protocol allows, for instance, the guided-recognition of structures through treated images or discriminating between healthy and unhealthy regions (e.g., early detection of cancer). In this framework, we study the potential of some polarimetric metrics, the so-called depolarization spaces, for the classification of biological tissues. The analysis is performed using 120 biological ex vivo samples of three different tissues types. Based on these data collection, we provide for the first time a comparison between these depolarization spaces, as well as with most commonly used depolarization metrics, in terms of biological samples discrimination. The results illustrate the way to determine the set of depolarization metrics which optimizes tissue classification efficiencies. In that sense, the results show the interest of the method which is general, and which can be applied to study multiple types of biological samples, including of course human tissues. The latter can be useful for instance, to improve and to boost applications related to optical biopsy.

Eigenvalue-based depolarization metric spaces for Mueller matrices.

We present a unified formal description and a detailed study of the depolarization spaces defined by various depolarization metrics based on the eigenvalues of the covariance matrix associated with a given Mueller matrix. By introducing natural generalizations of the common and Lorentz depolarization metrics, we likewise advance novel spaces appropriate for the description of extrinsic and intrinsic depolarization. We show the intimate relation existing between the depolarization spaces and the depolarization diagrams and solve the problem of the experimentally observed forbidden depolarization region. The theoretical developments are illustrated on numerical, analytical, and experimental examples of depolarizing Mueller matrices.

Quantitative depolarization measurements for fiber-based polarization-sensitive optical frequency domain imaging of the retinal pigment epithelium.

A full quantitative evaluation of the depolarization of light may serve to assess concentrations of depolarizing particles in the retinal pigment epithelium and to investigate their role in retinal diseases in the human eye. Optical coherence tomography and optical frequency domain imaging use spatial incoherent averaging to compute depolarization. Depolarization depends on accurate measurements of the polarization states at the receiver but also on the polarization state incident upon and within the tissue. Neglecting this dependence can result in artifacts and renders depolarization measurements vulnerable to birefringence in the system and in the sample. In this work, we discuss the challenges associated with using a single input polarization state and traditional depolarization metrics such as the degree-of-polarization and depolarization power. We demonstrate quantitative depolarization measurements based on Jones vector synthesis and polar decomposition using fiber-based polarization-sensitive optical frequency domain imaging of the retinal pigment epithelium in a human eye.

Differential description and irreversibility of depolarizing light–matter interactions

The widely used Jones and Mueller differential polarization calculi allow non-depolarizing deterministic polarization interactions to be described in an efficient way. Recently, the differential Mueller formalism has been successfully extended to the case of depolarizing transformations. In this article, a stochastic differential Jones formalism is shown to provide a clear physical insight on light depolarization, which arises when the interaction of polarized light with a medium involves randomized anisotropic properties. Based on this formalism, several intrinsic depolarization metrics which naturally arise to efficiently characterize light depolarization in a random medium are presented, and an irreversibility property of depolarizing transformations is finally established.

Characterization of natural and irradiated nails by means of the depolarization metrics.

Mueller polarimetry is applied to study the samples of nails: natural (or reference) and irradiated to 2 Gy ionizing radiation dose. We measure the whole Mueller matrices of the samples as a function of the scattering angle at a wavelength of 632.8 nm. We apply depolarization analysis to measured Mueller matrices by calculating the depolarization metrics [depolarization index, Q(M)-metric, first and second Lorenz indices, Cloude and Lorenz entropy] to quantify separability of the different samples of nails under study based on differences in their Mueller matrix. The results show that nail samples strongly depolarize the output light in backscattering, and irradiation in all cases results in increasing of depolarization. Most sensitive among depolarization metrics are the Lorenz entropy and Q(M)-metric.

Physically meaningful depolarization metric based on the differential Mueller matrix.

We present a novel depolarization metric for Mueller matrices based on the differential Mueller formalism. The proposed metric relies on the statistical interpretation of the differential Mueller matrix. We show that the differential depolarization index successfully quantifies depolarization even when applied to specific types of Mueller matrices for which some widely used depolarization metrics yield erroneous results. Moreover, the fact that the presented metric is directly linked to the variances and covariances of the elementary anisotropic properties of the sample makes it a valuable tool to quantify depolarization on a physically meaningful basis.

Characterization of porous media by means of the depolarization metrics

In this paper Mueller polarimetry is applied to study the samples with different porosity compacted from microcrystalline cellulose. We measure the whole Mueller matrices of the samples as a function of the incident angle at a wavelength of 632.8nm. To quantify separability of the different porous samples based on differences in their Mueller matrix behavior we apply depolarization and anisotropy analysis to measured Mueller matrices by calculating parameters characterizing depolarization (depolarization index, Q(M)-metric, first and second Lorenz indices, Cloude and Lorenz entropy) and anisotropy (values and azimuths of phase and amplitude anisotropy) properties of a sample. The results show that anisotropy parameters are almost completely insensitive to the range of porosity at least at 632.8nm. Whereas, all depolarization metrics considered are sensitive to the range of porosity. Most sensitive (not worst than 5%) among depolarization metrics are the Lorenz entropy and Q(M)-metric.

Dealing depolarization of light in Mueller matrices with scalar metrics

A number of depolarization metrics is applied to a series of reported Mueller matrices. It is shown the depolarization scalar metric Q( M) provides consistent results with the reported scalar metrics like the depolarization index and the degree of polarization. It is shown Q( M) provides additional information about the internal nature of the Mueller matrices, specifically when the upper limit, 3, is reached. It is also shown the depolarization index and the Q( M) metric are only necessary but not sufficient conditions for the physical realizability of Mueller matrices. Finally, Q( M) is proven to be consistent in all cases studied here.