Active Mode Single Pixel Imaging in the Highly Turbid Water Environment Using Compressive Sensing

Underwater imaging has always been a challenge due to limitations imposed by scattering and absorption nature of the underwater environment. The light would be highly degraded after reflection and propagation in the water medium. Being an advanced imaging technique, Single-pixel Imaging (SPI) is applicable to acquire object spatial information in low light, severe backscattering, and high absorption conditions. Combination of Compressive Sensing (CS) and SPI can overcome the limitation of SPI algorithms such as long data-acquisition time, low reconstruction efficiency and poor reconstruction quality. In the current research, an underwater SPI system based on CS is established to reconstruct our two-dimensional (2D) transparent object. We have systematically investigated the influence of water turbid degree, measurement pattern types and number of measurements on image reconstruction performance. The proposed system is capable to reconstruct the object even when the turbidity reaches up to 80 Nephelometric Turbidity Unit (NTU), where the conventional imaging systems are unusable. Proposed reconstruction method in our research can save more than 70% data acquisition time, compared to SPI algorithm. Our experimental setup has been compared to a conventional imaging system and an underwater ghost imaging system to show its efficiency in obtaining accurate results from turbid water conditions. Furthermore, various algorithm comparison and imaging enhancement studies demonstrates that our algorithm is superior in bringing highly convex optimization at a faster rate with a smaller number of measurements. This work creates new insight into the SPI application and generates a guideline for researchers to improve their applications.