Radiative transfer modeling and analysis of spatially variant and coherent illumination for undersea object detection

Bailey, B.C.; Blatt, Joel H.; Caimi, Frank M.

doi:10.1109/joe.2003.819152

Cited by 6 publications

(4 citation statements)

References 17 publications

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“…Methods using coherency of spatial gratings formed by structured lighting methods, such as proposed some years ago by Blatt and Caimi have not been investigated due to practical implementation problems (Bailey et al, 2003;Caimi et al, 1998).…”

Section: Spatial Coherency Techniquesmentioning

confidence: 99%

A Focus on Recent Developments and Trends in Underwater Imaging

Kocak¹,

Dalgleish²,

Caimi³

et al. 2008

mar technol soc j

231

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Section: Spatial Coherency Techniquesmentioning

confidence: 99%

A Focus on Recent Developments and Trends in Underwater Imaging

Kocak¹,

Dalgleish²,

Caimi³

et al. 2008

mar technol soc j

231

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show abstract

“…Underwater models for studying turbidity and illumination have been established, which is helpful for optical research of target detection and recognition in turbid waters. Bailey et al [44] proposed a model based on the spatial variation in underwater environments and coherent light and used it for low-contrast target detection in turbid water. This model was used to theoretically study the effects of turbidity, projection space-frequency variation, and three-dimensional target shapes on unstructured scattered light components and the target structured return signal.…”

Section: Underwater Image Processing Based On Polarization Imaging An...mentioning

confidence: 99%

A Survey of Target Detection and Recognition Methods in Underwater Turbid Areas

et al. 2022

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Based on analysis of state-of-the-art research investigating target detection and recognition in turbid waters, and aiming to solve the problems encountered during target detection and the unique influences of turbidity areas, in this review, the main problem is divided into two areas: image degradation caused by the unique conditions of turbid water, and target recognition. Existing target recognition methods are divided into three modules: target detection based on deep learning methods, underwater image restoration and enhancement approaches, and underwater image processing methods based on polarization imaging technology and scattering. The relevant research results are analyzed in detail, and methods regarding image processing, target detection, and recognition in turbid water, and relevant datasets are summarized. The main scenarios in which underwater target detection and recognition technology are applied are listed, and the key problems that exist in the current technology are identified. Solutions and development directions are discussed. This work provides a reference for engineering tasks in underwater turbid areas and an outlook on the development of underwater intelligent sensing technology in the future.

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“…The laser beam can also be modulated in spatial domain. The spatial interferometric projection is such a technique developed by the Harbor Branch Oceanographic Institution (Bailey, Blatt, & Caimi, 2003).…”

Section: Interferometric Projectionmentioning

confidence: 99%

“…The backscattering BB backsc is the most primary noise in an illumination scheme. Referring to the geometry in , its two components are determined by the equations (Bailey, 2002), α is the angle between the path of integration and the target plan,…”

Section: Interferometric Projectionmentioning

confidence: 99%

Laser scanning imaging system for underwater robotics vehicle

Xu¹

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In recent years, underwater robotics vehicles (URVs), including remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs), are growing rapidly in deployment for both commercial and military applications. Among various imaging approaches used in these vehicles, optical vision has shown great advantages in intuitive representation and extremely high resolution, when compared with a popular alternative like acoustic imaging. Unfortunately, optical images are severely degraded due to the absorption and scattering of light in turbid water environments. Performance of a conventional camera system directly depends on the turbidity of water. Green laser has been used as an active light source because of its good transmittance in water and its high output power. At present, novel lighting and imaging systems, such as laser galvanometer scanning systems and range-gated systems have shown some achievements in minimizing light scattering effects. However, their unwieldy sizes and high power consumptions limit their usages on small URVs. This thesis discusses a low-powered and low-speed scanning scheme, which has an adjustable illumination volume to fit various water turbidities. The illumination beam can be concentrated to improve image signal-to-noise ratio in turbid water, and expanded to improve frame update rate in clear water. The scheme has advantages in simple structure, compact size, and low power consumption. An illumination model is developed to analyze the relationship between light flux, illumination volume, and water turbidity. It focuses on highly turbid water condition, and assumes that forward and backward scattered fluxes uniformly fill all forward and backward directions. Light propagation is divided into two stages: from light source to object, and from object to camera. The light flux in each stage is regarded as a linear superposition of transmitted, forward-scattered, and backscattered components, which are individually calculated with volume scattering function and Bouguer's law. The model differs from existing models as it considers geometric parameters in an illumination scene. It quantitatively reveals how illumination volume affects the distributions of flux components. When a light beam is being expanded, the total flux received by a camera increases, and backscattered component increases faster than the correctly transmitted (or desired) component. When a wide illumination beam is used in turbid water, the signal strength of the scattered noise may exceed that of the desired signal component. This makes the objects undetectable.

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Radiative transfer modeling and analysis of spatially variant and coherent illumination for undersea object detection

Cited by 6 publications

References 17 publications

A Focus on Recent Developments and Trends in Underwater Imaging

A Focus on Recent Developments and Trends in Underwater Imaging

A Survey of Target Detection and Recognition Methods in Underwater Turbid Areas

Laser scanning imaging system for underwater robotics vehicle

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