Passive Polarimetric Imaging Research Articles

Polarimetric modeling and measurement approach for refractory material in the mid-wave infrared

Passive polarimetric imaging has gained substantial attention over the past three decades in various applications in defense. The complexity of polarimetry modeling and measurement in the thermal infrared exceeds that of the visible and near-infrared due to the complementary polarization orientation of reflected and emitted radiance. This paper presents a comprehensive polarimetric radiance model and a degree of linear polarization (DOLP) model, both of which are specifically tailored for the infrared spectrum, accounting for both reflected and emitted radiance. Building on this foundation, we conduct an analysis and simulation of the DOLP’s variation as the object temperature changes. This analysis enables the observation of relationships that can be strategically utilized in subsequent experiments focused on measuring polarized model parameters. To mitigate the influence of reflected radiance components, the samples are subjected to high temperatures. The observed Stokes images from the sample surfaces are normalized to eliminate the dependence of each Stokes image on temperature. This parameters acquisition measurement method is particularly well-suited for refractories. Finally, the efficacy of the polarized model parameters acquisition technique is demonstrated through experiments involving three distinct refractory materials in the MWIR.

Passive polarimetric imaging of millimeter and terahertz waves for personnel security screening.

Passive millimeter and terahertz wave imaging is a powerful way for personnel security inspection and scene monitoring. The existing systems usually have a single polarization mode. To obtain more information, polarimetric imaging has been preliminarily explored recently. However, there is no work exhibiting high-performance polarimetric imaging to analyze and interpret polarization characteristics. In this Letter, we report on the development of a W-band passive polarimetric imaging system for human body screening and present the polarization characteristics analysis of several typical scenarios. The experimental system has a spatial resolution of better than 2 cm at 2.5 m distance and has a thermal sensitivity of better than 0.3 K. The system can display polarization properties of human bodies and concealed objects. The experimental results demonstrate that passive polarimetric imaging has a great potential for object contrast enhancement, detection, segmentation, and recognition.

Hybrid passive polarimetric imager and lidar combination for material classification

We investigate the augmentation of active imaging with passive polarimetric imaging for material classification. Experiments are conducted to obtain a multimodal dataset of lidar reflectivity and polarimetric thermal self-emission measurements against a diverse set of material types. Using the assumption that active lidar imaging can provide high-resolution three-dimensional spatial information, a known surface orientation is utilized to enable higher fidelity classification. Machine learning is applied to the dataset of monostatic lidar unidirectional reflectivity and passive longwave infrared degree of linear polarization features for material classification. The hybrid sensor technique can classify materials with 91.1% accuracy even with measurement noise resulting in a signal-to-noise ratio of only 6 dB. The application of the proposed technique is applicable for the classification of hidden objects or could assist existing spatial-based object classification.

Review of visualization methods for passive polarization imaging

Collected sources for the different types of visualizations used in the field of polarization imaging are not extensive. Here, we survey and review the different visualization techniques in passive polarimetric imaging. Analysis of the methods is done by applying various concepts from the field of visualization. We provide recommendations for choosing a visualization based on the data structure, spatial frequency, and analysis goals.

Contrast optimization in broadband passive polarimetric imaging based on color camera.

Broadband polarimetric imaging consists of forming an image under spectrally wide illumination after having optimized the polarization state analyzer (PSA) to maximize the target/background discriminability. In previous works, the image sensor was monochrome, and only the intensity contrast was optimized. However, due to its spectrally varying response, the PSA not only changes the light's intensity, but also its color. This color information can serve as a further parameter to improve discrimination. In this paper, we employ a color camera in a broadband Stokes (passive) polarimetric imaging system and take into color difference's contribution to discrimination ability in optimizing the PSA setting. We show through experiments that a significant improvement of discrimination ability over monochrome imaging is obtained, especially when there are multiple objects in the scene.

Contrast optimization in broadband passive polarimetric imaging.

Polarimetric imaging is often performed using light with a narrow spectrum for the sake of polarization measurement accuracy. However, due to the use of narrowband filters, this reduces the amount of light entering the system and thus the signal-to-noise ratio. This may not be the best choice for target detection applications, where a high target contrast is required rather than polarimetric accuracy. We address contrast optimization for broadband passive polarimetric imaging. We show through simulation and experiments that polarimetric contrast can be significantly increased by broadening the spectrum of analyzed light. In addition, we show that the contrast can be optimized by taking into account the spectral dependence of the scene and of the polarization analysis devices.