KEYWORDS: Polarization, Cameras, Time correlated single photon counting, Imaging systems, Reflection, Underwater imaging, Time of flight imaging, Polarimetry, Photon polarization, Optical systems
Underwater imaging is crucial for many applications, from marine biology research to industrial inspections, oil and gas exploration, search-and-rescue operations, and defense and security. Yet, underwater imaging poses numerous challenges, including backscatter from suspended particles, light absorption, and distortion caused by the medium's varying optical properties, in which traditional imaging methods often fall short. To address these challenges, we exploit the polarization properties of light by integrating a unique polarization-demultiplexing metasurface with an imager. Both direct imaging using a conventional CCD camera and a time-of-flight single-photon counting camera are used. By correlating the polarization states of emitted and reflected light, our approach enables us to develop means to enhance image contrast and achieve a more accurate estimation of the true target depth.
Polarimetry is pivotal in analyzing light's polarization properties, with vast potential in areas like remote sensing, material analysis, biological imaging, medical diagnostics, and defense. Metasurfaces, finely engineered to control light's phase, amplitude, and polarization, present an innovative platform to augment polarized light examination. This study delves into the design, fabrication, and practical demonstration of these metasurfaces, showcasing their use in polarization demultiplexing and subsequent imaging reconstruction. Experimentally, we used metasurfaces to observe an underwater scene under varied polarized light sources. This allows the selective capture of distinct polarizations simultaneously, elevating the accuracy of polarimetric measurements. A more in-depth discussion on image reconstruction via Stokes parameters is provided.
Active illumination with underwater laser imaging has unique advantages for the identification of underwater objects, especially in shallow waters, complex marine environments and inaccessible locations. However, backscattered light from the water particulates can blur the resulting laser images. To improve the quality of underwater laser images, we have examined a wide range of image enhancement (IE) and restoration (IR) techniques. In our recent prior work, we have experimentally evaluated the efficacy of over 20 IE/IR methods specifically for the underwater object recognition, examining the impact of artifacts introduced by IE/IR on the deep neural network (DNN) architecture required for optimal classification accuracy. This paper builds on this work by considering the effect of polarization on underwater image restoration and object recognition. Using a one-of-a-kind multi-polarization underwater laser image dataset, this paper examines the image of polarization on the efficacy of IE/IR algorithms and proposes a deep neural network (DNN) for fusing and jointly exploiting the multi-polarization data for improved underwater object recognition.
Polarimetry imaging technology has progressed rapidly in recent years. It promises advances in various fields of application, including remote sensing, medical imaging, molecular sensing, and many areas of defense and homeland security application. Conventional polarimetry is not flexible and has remained difficult to implement due to the complexity of optics and moving parts, and generally, it is bulky and costly. Recent advances in the design, micro/nanofabrication, and testing of metasurfaces have opened tremendous opportunities by simplifying the optics pathway. These sub-wavelength and flat structures can be engineered to transform the propagation, phase, and polarization of light. It is now conceivable to replace the carefully aligned optical components with a single well-designed metasurface. In this work, we present the design, fabrication, and integration of a multiplexed dielectric metasurface operating at 532 nm, which is of great interest for underwater imaging. The metasurface developed in this work spatially diffracts polarizations, resulting in demultiplexing the polarization, and the intensity of each polarization was recorded to determine the Stokes parameters. We will discuss the optimization process of designing the dielectric metasurface to recover the Stokes parameters for imaging and the degree of polarization. With the FDTD simulation, we explored the metasurface design parameter space to achieve better transmission and phase control. The incorporation of Pancharatnam–Berry phase and cross-talk among the orthogonal components of linearly and circularly polarized light were evaluated. The designed metasurface was fabricated using electron beam lithography and ICP-RIE etching. Finally, the fabricated metasurface was integrated with a time-of-flight multi-pixel imager.
Active illumination with underwater laser imaging has unique advantages for the identification of underwater objects, especially in shallow waters, complex marine environments and inaccessible locations. Laser intensity images embody valuable information that can be utilized for object recognition; however, backscattered light from the water column and other particulates blur the resulting laser images, rendering the objects in the images unintelligible. Although over the years a variety of deblurring and other image restoration and enhancement algorithms have been proposed, these works primarily consider optical images of scenery, not monotone underwater images of objects, for which contours are more critical. This work proposes the utilization of edge metrics to evaluate the efficacy of image restoration and enhancement algorithms for underwater laser images. Our results provide insight into the best methods for improving underwater laser image quality for object recognition.
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