Holographic and polarization features analysis for microplastics characterization and water monitoring

Abstract

The assessment of microplastics (MPs) pollution and water quality monitoring raise a lot of attention in recent years. Discriminative methods are highly needed for quick and accurate in situ MP detections. Digital holography records the wavefront information of the objects and contains the morphology, refractive index, and roughness information. Polarization imaging inspects the optical anisotropy of MPs, which is related to their birefringence and material characteristics. In this work, we explore the capability of holographic and polarization imaging for the identification of MPs. The computed features, such as the angle of polarization (AoP) and degree of linear polarization (DoLP), show distinguishable characteristics of MPs. We inspect the method feasibility on MP classification as well as biological and natural particles. The proposed method shows potential use in real-time, non-contact in situ MPs detection and water pollution monitoring.

Snapshot Polarization-Sensitive Holography for Detecting Microplastics in Turbid Water

“…One of the main reasons is that the features employed for MP classification are relatively limited. To obtain more meaningful information and extract more distinguishable features about environmental samples, a promising approach is the integration of holographic imaging and polarization imaging. − Consequently, the specificity of the detection system can be considerably enhanced. There are notable examples that have explored the implementation of polarization imaging through holographic approaches, − highlighting the potential for combining these two imaging modalities.…”

“…In particular, Tahara et al − developed a hybrid system coupling incoherent digital holography with polarization imaging, showcasing promising results on polarization-sensitive 3D imaging. Nevertheless, there are very few works on the integration of holography and polarimetry for the detection of MPs. , Běhal et al and Valentino et al have contributed the preliminary attempt at such a strategy. , They built a hybrid system based on off-axis holographic imaging and two-step Jones matrix polarimetry, demonstrating promising results for the identification of MP fibers. Meanwhile, Zhu et al and Li et al are also developing different integrated imaging systems with more compact and automatic configurations. ,− In their works, customized fluidic channel and deep learning-based classifiers are adopted to realize high-throughput and dynamic assessment of MPs.…”