
Depolarizing metrics for plant samples imaging
Author(s) -
Albert Van Eeckhout,
Enric Garcia-Caurel,
Teresa Garnatje,
Mercè Durfort,
Juan C. Escalera,
José Luis Vidal,
José J. Gil,
Juan Campos,
Ángel Lizana
Publication year - 2019
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0213909
Subject(s) - polarimetry , mueller calculus , depolarization , hyperspectral imaging , polarization (electrochemistry) , context (archaeology) , optics , remote sensing , polarimeter , characterization (materials science) , biological system , computer science , physics , artificial intelligence , biology , scattering , chemistry , geography , biophysics , paleontology
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.