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.

Ultrasound has been proven to be a valid tool for ranging, especially in water. In this paper, we design a high-resolution ultrasonic ranging system that uses a thin laser beam as an ultrasonic sensor. The laser sensing provides a noncontact method for ultrasound detection based on acousto-optic diffraction. Unlike conventional methods, the ultrasound transmitted from the transducer is recorded as the reference signal when it first passes through the laser. It can be used to improve the accuracy and resolution of the time-of-flight (TOF) by a cross-correlation method. Transducers with a central frequency of 1 MHz and diameters of 20 mm and 28 mm are used in the experiment. Five targets and a test piece are used to evaluate the ranging performance. The sound velocity is measured by the sound velocity profiler (SVP). The repeatability error of TOF is less than 4 ns, and the theoretical resolution of TOF is 0.4 ns. The results show a measurement resolution within one-tenth of the wavelength of ultrasound and an accuracy better than 0.3 mm for targets at a distance up to 0.8 m. The proposed system has potential applications in underwater ranging and thickness detection.

Polarization characteristics are significantly crucial for tasks in various fields, including the remote sensing of oceans and atmosphere, as well as the polarization LIDAR and polarimetric imaging in scattering media. Many polarimetric metrics (such as the degree of polarization, polarization angle diattenuation, and depolarization) have been proposed to enrich the characterization and improve the task performance in scattering media; yet, their related efficacy is limited, especially in high turbidity conditions. The indices of polarimetric purity (IPPs), including three different depolarization metrics, have been successfully applied to biomedical diagnosis. However, it is still debatable whether IPPs also are excellent metrics for identifying or distinguishing objects in scattering media. In this work, we seek to provide physical insights into the application of distinguishing and identifying different objects via IPPs. Imaging experiments are devised and performed on different objects, e.g., metals and plastics, under different turbidity levels, demonstrating the superiority of IPPs as excellent metrics for object identification in scattering conditions. The experimental results show that the IPPs images can enhance image contrast and improve discriminability, as well as break the limitation of traditional intensity-model imaging techniques when further combined with dehazing or enhancing algorithms. Importantly, as the used Mueller matrix (MM) and the related IPPs can also be obtained via other types of MM polarimeters (e.g., PolSAR and MM microscopy), the proposed solution and idea have potential for such applications as biomedical imaging, photogrammetry, and remote sensing.

We present a new method to measure the velocity of sound in pure water and seawater using the Raman-Nath diffraction caused by acousto-optic effect between the optical frequency comb and the ultrasonic pulse. In the Mach-Zehnder interferometry system we established, the measurement and reference arms are tagged with sharp negative pulses caused by the pulsed ultrasound passing through them. The difference in optical path between the two parallel beams is twice the flight distance of the ultrasonic waves. The span between the two negative pulses reflects the time interval. At the same time, the distance between the two arms can be measured precisely using the femtosecond laser interferometry. Consequently, the time interval and the distance can be used to measure the sound velocity. The experimental results show that, the uncertainty of the sound speed measurement can achieve 0.03m/s@1482m/s in pure water and 0.029m/s@1527m/s in seawater, respectively, compared with the commercial sound velocity profiler (SVP). More importantly, benefiting from the faster and cleaner response of the acousto-optic effect than the piezoelectric effect which is widely adopted in direct sound velocity measurement method, our method provides a new idea for the metrology of sound velocity in seawater.

The navigation and localization of autonomous underwater vehicles (AUVs) in seawater are of the utmost importance for scientific research, petroleum engineering, search and rescue, and military missions concerning the special environment of seawater. However, there is still no general method for AUVs navigation and localization, especially in the featureless seabed. The reported approaches to solving AUVs navigation and localization problems employ an expensive inertial navigation system (INS), with cumulative errors and dead reckoning, and a high-cost long baseline (LBL) in a featureless subsea. In this study, a simultaneous localization and mapping (AMB-SLAM) online algorithm, based on acoustic and magnetic beacons, was proposed. The AMB-SLAM online algorithm is based on multiple randomly distributed beacons of low-frequency magnetic fields and a single fixed acoustic beacon for location and mapping. The experimental results show that the performance of the AMB-SLAM online algorithm has a high robustness. The proposed approach (the AMB-SLAM online algorithm) provides a low-complexity, low-cost, and high-precision online solution to the AUVs navigation and localization problem in featureless seawater environments. The AMB-SLAM online solution could enable AUVs to autonomously explore or autonomously intervene in featureless seawater environments, which would enable AUVs to accomplish fully autonomous survey missions.