Underwater Optical Imaging Systems: A Comprehensive Review of Technologies, Architectures and Mission-Driven Design Trade-Offs

Abstract

Underwater optical imaging plays a crucial role in marine exploration, ecological monitoring, underwater inspection, autonomous navigation, and scientific research, but it is heavily restricted by wavelength-dependent attenuation, scattering, refraction, and low visibility. This comprehensive review examines underwater optical imaging from a system-design perspective, integrating the physical principles of underwater light propagation with imaging modalities, illumination strategies, sensing technologies, computational methods, and system-level implementation considerations. A structured literature search was conducted using Scopus and Google Scholar, yielding 441 initially identified studies, of which 262 were retained after screening according to the defined inclusion and exclusion criteria, and seven additional recent studies were incorporated during revision, resulting in a final set of 269 publications. The reviewed literature is organized according to imaging modality and system architecture, including conventional RGB imaging, laser-based imaging, polarization imaging, multispectral and hyperspectral imaging, computational imaging, and AI-assisted approaches. Emphasis is placed on the relationship between environmental conditions, mission requirements, imaging range, illumination geometry, calibration, processing location, computational demand, and platform constraints. The analysis shows that no single imaging modality provides optimal performance across all underwater environments. Instead, effective system design requires matching the sensing and illumination strategy to water conditions, target distance, required image quality, available power, computational resources, and real-time requirements. The review therefore proposes a mission-oriented framework for understanding the principal trade-offs involved in the design and selection of underwater optical imaging systems and identifies adaptive acquisition, multimodal sensing, physics-informed AI, and optical–computational co-design as important directions for future development.