We highlight the interest of using the indices of polarimetric purity (IPPs) to the inspection of biological tissues. The IPPs were recently proposed in the literature and they result in a further synthetization of the depolarizing properties of samples. Compared with standard polarimetric images of biological samples, IPP-based images lead to larger image contrast of some biological structures and to a further physical interpretation of the depolarizing mechanisms inherent to the samples. In addition, unlike other methods, their calculation do not require advanced algebraic operations (as is the case of polar decompositions), and they result in 3 indicators of easy implementation. We also propose a pseudo-colored encoding of the IPP information that leads to an improved visualization of samples. This last technique opens the possibility of tailored adjustment of tissues contrast by using customized pseudo-colored images. The potential of the IPP approach is experimentally highlighted along the manuscript by studying 3 different ex-vivo samples. A significant image contrast enhancement is obtained by using the IPP-based methods, compared to standard polarimetric images.

In this work, we discuss the interest of using the indices of polarimetric purity (IPPs) as a criterion for the characterization and classification of depolarizing samples. We prove how differences in the depolarizing capability of samples, not seen by the commonly used depolarization index P, are identified by the IPPs. The above-stated result is analyzed from a theoretical point of view and experimentally verified through a set of polarimetric measurements. We show how the approach presented here can be useful in easily synthetizing depolarizing samples with controlled depolarizing features, just by properly combining low-cost fully polarizing elements (such as linear retarders or polarizers).

Optical methods, as fluorescence microscopy or hyperspectral imaging, are commonly used for plants visualization and characterization. Another powerful collection of optical techniques is the so-called polarimetry, widely used to enhance image contrast in multiple applications. In the botanical applications framework, in spite of some works have already highlighted the depolarizing print that plant structures left on input polarized beams, the potential of polarimetric methods has not been properly exploited. In fact, among the few works dealing with polarization and plants, most of them study light scattered by plants using the Degree of Polarization (DoP) indicator. Other more powerful depolarization metrics are nowadays neglected. In this context, we highlight the potential of different depolarization metrics obtained using the Mueller matrix (MM) measurement: the Depolarization Index and the Indices of Polarimetric Purity. We perform a qualitative and quantitative comparison between DoP- and MM-based images by studying a particular plant, the Hedera maroccana. We show how Mueller-based metrics are generally more suitable in terms of contrast than DoP-based measurements. The potential of polarimetric measurements in the study of plants is highlighted in this work, suggesting they can be applied to the characterization of plants, plant taxonomy, water stress in plants, and other botanical studies.

Optical microscopy techniques for plant inspection benefit from the fact that at least one of the multiple properties of light (intensity, phase, wavelength, polarization) may be modified by vegetal tissues. Paradoxically, polarimetric microscopy although being a mature technique in biophotonics, is not so commonly used in botany. Importantly, only specific polarimetric observables, as birefringence or dichroism, have some presence in botany studies, and other relevant metrics, as those based on depolarization, are underused. We present a versatile method, based on a representative selection of polarimetric observables, to obtain and to analyse images of plants which bring significant information about their structure and/or the spatial organization of their constituents (cells, organelles, among other structures). We provide a thorough analysis of polarimetric microscopy images of sections of plant leaves which are compared with those obtained by other commonly used microscopy techniques in plant biology. Our results show the interest of polarimetric microscopy for plant inspection, as it is non-destructive technique, highly competitive in economical and time consumption, and providing advantages compared to standard non-polarizing techniques.

We highlight the potential of a predictive optical model method for tissue recognition, based on the statistical analysis of different polarimetric indicators that retrieve complete polarimetric information (selective absorption, retardance and depolarization) of samples. The study is conducted on the experimental Mueller matrices of four biological tissues (bone, tendon, muscle and myotendinous junction) measured from a collection of 157 ex-vivo chicken samples. Moreover, we perform several non-parametric data distribution analyses to build a logistic regression-based algorithm capable to recognize, in a single and dynamic measurement, whether a sample corresponds (or not) to one of the four different tissue categories.