Sidewall roughness-caused optical loss of waveguides is one of the critical limitations to the proliferation of the silicon photonic integrated circuits in fiber-optic communications and optical interconnects in computers, so it is imperative to investigate the distribution characteristics of sidewall roughness and its impact upon the optical losses. In this article, we investigated the distribution properties of waveguide sidewall roughness (SWR) with the analysis for the three-dimensional (3-D) SWR of dielectric waveguides, and, then the accurate SWR measurements for silicon-on-insulator (SOI) waveguide were carried out with confocal laser scanning microscopy (CLSM). Further, we composed a theoretical/experimental combinative model of the SWR-caused optical propagation loss. Consequently, with the systematic simulations for the characteristics of optical propagation loss of SOI waveguides, the two critical points were found: (i) the sidewall roughness-caused optical loss was synchronously dependent on the correlation length and the waveguide width in addition to the SWR and (ii) the theoretical upper limit of the correlation length was the bottleneck to compressing the roughness-induced optical loss. The simulation results for the optical loss characteristics, including the differences between the TE and TM modes, were in accord with the experimental data published in the literature. The above research outcomes are very sustainable to the selection of coatings before/after the SOI waveguide fabrication.

Spectral–polarization imaging technology plays a crucial role in remote sensing detection, enhancing target identification and tracking capabilities by capturing both spectral and polarization information reflected from object surfaces. However, the acquisition of multi-dimensional data often leads to extensive datasets that necessitate comprehensive analysis, thereby impeding the convenience and efficiency of remote sensing detection. To address this challenge, we propose a fusion algorithm based on spectral–polarization characteristics, incorporating principal component analysis (PCA) and energy weighting. This algorithm effectively consolidates multi-dimensional features within the scene into a single image, enhancing object details and enriching edge features. The robustness and universality of our proposed algorithm are demonstrated through experimentally obtained datasets and verified with publicly available datasets. Additionally, to meet the requirements of remote sensing tracking, we meticulously designed a pseudo-color mapping scheme consistent with human vision. This scheme maps polarization degree to color saturation, polarization angle to hue, and the fused image to intensity, resulting in a visual display aligned with human visual perception. We also discuss the application of this technique in processing data generated by the Channel-modulated static birefringent Fourier transform imaging spectropolarimeter (CSBFTIS). Experimental results demonstrate a significant enhancement in the information entropy and average gradient of the fused image compared to the optimal image before fusion, achieving maximum increases of 88% and 94%, respectively. This provides a solid foundation for target recognition and tracking in airborne remote sensing detection.

In this paper, infrared polarization detection information acquisition technology is proposed, and the polarization characteristics of oil spills are modeled and studied. A set of long-wave infrared polarization detection equipment for oil spills is designed and built, and modeling research on oil spill polarization characteristics is carried out to accurately detect and identify oil spill types and for the faster processing of oil spill events. Oil spill accuracy is increased by defining the polarization maintenance method of the polarization optical system and reducing the polarization measurement error brought on by the imaging system. As a result, a higher than 3% contrast exists between the polarization degree image and the corrected infrared intensity image. Outdoor tests using oil, palm oil, crude oil, gasoline, and diesel oil spill types are carried out in a controlled environment to collect data on the polarization of various oil species. According to the findings, each oil species’ infrared polarization contrast with seawater is typically greater than its infrared intensity contrast. However, the polarization data of saltwater, diesel, and palm oil, which are difficult to identify in intensity data, show a noticeable difference, further proving the viability of utilizing polarization to discern oil spills.

The polarised Bidirectional Reflectance Distribution Function (pBRDF) model relates the properties of target materials to the polarisation information of the incident and reflected light. The Priest–Germer (P-G) model was the first strictly pBRDF model to be officially released; however, some shortcomings remain. In this study, we first analyse the assumption framework of the P-G model, analyse the assumption framework to determine the imperfections in the framework, supplement the boundary conditions of the model for diffraction and transmission effects, and propose and construct a polarised pBTDF model based on the existing P-G model and parameter inversion; the output results of the model are compared with the experimental data through simulation. The results show that the intensity relative error and Degree of Linear Polarisation relative error of the target can be reduced by more than 40%, using the improved model, proving its accuracy and precision.

With the development of all‐optical networks, all‐optical devices have become a research hotspot in recent years. Two‐dimensional materials, represented by graphene and black phosphorus, have attracted great interest in the scientific community due to their excellent optical, electrical, magnetic, and mechanical properties. Bridging the gap between fiber optics and nanotechnology, microfibers can interact with light and matter at the micro or even nanoscale. By combining two‐dimensional materials with microfibers, composite waveguides can be formed. They have the advantages of high nonlinear effect, all‐fiber structure, and high damage threshold, etc. The composite waveguide can be directly applied to optical fiber communication systems, and plays an important role in the field of all‐optical signal processing with a huge application prospect. In this review, the properties of typical 2D materials are first introduced. Next, the preparation methods of the relevant equipments are introduced and compared. Then, the all‐optical signal processing technology based on 2D material‐integrated microfiber composite waveguide is reviewed. The latest developments of all‐optical modulators, all‐optical wavelength converters, all‐optical logic gates and all‐optical thresholding devices are presented. Finally, the challenges and opportunities for the future development of 2D materials‐integrated microfiber optoelectronic devices are summarized.