Distributed optical fiber sensors (DOFS) offer unprecedented features, the most unique one of which is the ability of monitoring variations of the physical and chemical parameters with spatial continuity along the fiber. Among all these distributed sensing techniques, optical frequency domain reflectometry (OFDR) has been given tremendous attention because of its high spatial resolution and large dynamic range. In addition, DOFS based on OFDR have been used to sense many parameters. In this review, we will survey the key technologies for improving sensing range, spatial resolution and sensing performance in DOFS based on OFDR. We also introduce the sensing mechanisms and the applications of DOFS based on OFDR including strain, stress, vibration, temperature, 3D shape, flow, refractive index, magnetic field, radiation, gas and so on.

Protein assays show great importance in medical research and disease diagnoses. Liquid crystals (LCs), as a branch of sensitive materials, offer promising applicability in the field of biosensing. Herein, we developed an ultrasensitive biosensor for the detection of low-concentration protein molecules, employing LC-amplified optofluidic resonators. In this design, the orientation of LCs was disturbed by immobilized protein molecules through the reduction of the vertical anchoring force from the alignment layer. A biosensing platform based on the whispering-gallery mode (WGM) from the LC-amplified optofluidic resonator was developed and explored, in which the spectral wavelength shift was monitored as the sensing parameter. The microbubble structure provided a stable and reliable WGM resonator with a high Q factor for LCs. It is demonstrated that the wall thickness of the microbubble played a key role in enhancing the sensitivity of the LC-amplified WGM microcavity. It is also found that protein molecules coated on the internal surface of microbubble led to their interactions with laser beams and the orientation transition of LCs. Both effects amplified the target information and triggered a sensitive wavelength shift in WGM spectra. A detection limit of 1 fM for bovine serum albumin (BSA) was achieved to demonstrate the high-sensitivity of our sensing platform in protein assays. Compared to the detection using a conventional polarized optical microscope (POM), the sensitivity was improved by seven orders of magnitude. Furthermore, multiple types of proteins and specific biosensing were also investigated to verify the potential of LC-amplified optofluidic resonators in the biomolecular detection. Our studies indicate that LC-amplified optofluidic resonators offer a new solution for the ultrasensitive real-time biosensing and the characterization of biomolecular interactions.

Circular polarization memory is a well-known phenomenon indicating that the circular polarization light can persist better its polarization property during propagating through turbid media compared with the linear polarization light. Therefore, in principle, using circularly polarized light can probably improve the quality of image recovery in dense turbid media than using the linearly polarized light. In this paper, we propose a new polarimetric image recovery method in dense turbid media with the illumination light of circular polarization, and we realize the image recovery combining the circular polarization information and linearly polarization information. The real-world experiment results demonstrate that the proposed method is more effective than previous methods, including the traditional polarimetric image recovery method by Schechner’s [Appl. Opt. 42, 511 (2003)] based on linear polarization.

The underwater imaging could be severely degraded by the scattering media due the backscatter veiling and signal attenuation. Image recovery based on polarization information has shown its efficiency in improving the quality of image in scattering medium, but few of them considered the effect of non-uniform optical field on the image recovery. In this paper, we consider the condition of non-uniform optical field, and we propose a method of retrieving the objects radiance based on estimating the degree of polarization (DOP) and the intensity of backscatter at different positions of the image. The experimental results demonstrate that the quality of the underwater image can be effectively enhanced by this method. In addition, compared with the previous methods, the method proposed in this paper can maintain a better performance at different positions of the image, thanks to considering the DOP and intensity of backscatter as spatial variables instead of constants.

In unmanned monitoring such as perimeter security, pipeline detection, railway security, and so on, it is still a challenging task to accurately locate the irregular vibration events. Compared with traditional vibration detection technologies, distributed optical fiber vibration sensors (DOFVSs) have superior advantages such as high spatial resolution, large monitoring range, good concealment, excellent flexibility, and simple sensing structure. The DOFVS can be mainly classified into two types, i.e., the interferometer-based DOFVS (IDOFVS) and the backscattering-based DOFVS (BDOFVS). In particular, IDOFVS has unique sensing advantages, such as high stability, simple structure, high sensitivity, and wide frequency response. In this article, the development of long-distance IDOFVS in recent years has been summarized. The sensing principle of IDOFVS has been theoretically explained. The specific classification of the IDOFVS and the corresponding sensing structures are described in detail. In addition, the long-distance distributed vibration sensing structure and processing algorithms, such as denoising and locating algorithms, are analyzed. Finally, the performance of recent long-distance IDOFVS has been compared and the development direction has been discussed.

Polarization can provide information largely uncorrelated with the spectrum and intensity. Therefore, polarimetric imaging (PI) techniques have significant advantages in many fields, e.g., ocean observation, remote sensing (RS), biomedical diagnosis, and autonomous vehicles. Recently, with the increasing amount of data and the rapid development of physical models, deep learning (DL) and its related technique have become an irreplaceable solution for solving various tasks and breaking the limitations of traditional methods. PI and DL have been combined successfully to provide brand-new solutions to many practical applications. This review briefly introduces PI and DL’s most relevant concepts and models. It then shows how DL has been applied for PI tasks, including image restoration, object detection, image fusion, scene classification, and resolution improvement. The review covers the state-of-the-art works combining PI with DL algorithms and recommends some potential future research directions. We hope that the present work will be helpful for researchers in the fields of both optical imaging and RS, and that it will stimulate more ideas in this exciting research field.