Polarimetric Imaging Through Scattering Media: A Review

Abstract

Imaging in scattering media has been a challenging and important subject in optical science. In scattering media, the image quality is often severely degraded by the scattering and absorption effects owing to the small particles and the resulting nonuniform distribution of the intensity or polarization properties. This study reviews the recent development in polarimetric imaging techniques that address these challenges. Specifically, based on the polarization properties of the backscattering light, polarimetric methods can estimate the intensity level of the backscattering and the transmittance of the media. They can also separate the target signal from the undesired ones to achieve high-quality imaging. In addition, the different designs of the polarimetric imaging systems offer additional metrics, for example, the degree/angle of polarization, to recover images with high fidelity. We first introduce the physical degradation models in scattering media. Secondly, we apply the models in different polarimetric imaging systems, such as polarization difference, Stokes vector, Mueller matrix, and deep learning-based systems. Lastly, we provide a model selection guideline and future research directions in polarimetric imaging.

Spatial helicity response metric to quantify particle size and turbidity of heterogeneous media through circular polarization imaging

“…For example, knowledge that a measurable contribution of the flipped signal arises from scattering in the first few microns of a sample may enable superficial polarimetric sampling of tissues (where many pathologies arise such as tooth decay 50 and skin cancers 51 ). Moreover, further understanding of these propagation pathways may prove fruitful in imaging applications for improved contrast in turbid media 38 , 39 , 52 , 53 .…”

Snapshot Polarization-Sensitive Holography for Detecting Microplastics in Turbid Water

“…The integration of two powerful computational imaging techniques enables the fast and accurate characterization and identification of MPs while maintaining a simple optical configuration. An efficient computational method based on polarization parameters, i.e., degree of linear polarization (DoLP) and angle of polarization (AoP), 38 is proposed to recognize MP particles through scattering media and quantify the optical anisotropy of MP materials. The results demonstrate that AoP can effectively improve image contrast for accurate particle segmentation even in highly turbid water.…”

Photoelastic and Stokes images through deep convolutional neural networks: a comparison of stress fields

“…On the other hand, some other representations have been used to analyze light polarization, such as thermal imaging based on polarimetry 6 or polarization microscopy images for biomedical applications 7 . Some authors have even applied deep learning models to various polarimetric imaging systems, such as polarization difference, Stokes vector and Mueller matrix 8 .…”