Laser imaging through scattering media

Giakos, G.C.; Molhokar, A.; Orozco, A.; Kumar, V.; Sumrain, S.; Mehta, Dalip Singh; Maniyedath, A.; Ojha, Nirdesh; Medithe, A.

doi:10.1109/imtc.2004.1351081

Cited by 3 publications

(3 citation statements)

References 12 publications

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“…Subsurface polarization imaging of different objects in turbid media has been intensively studied in different fields such as target detection, ocean optics, medical imaging and diagnostics [1][2][3][4][5][6][7][8]. The enhancement of image optical contrast provided by various polarimetric imaging techniques (Mueller matrix, differential polarization, degree of polarization…) was evaluated by comparison with standard intensity imaging.…”

Section: Introductionmentioning

confidence: 99%

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Sources of possible artefacts in the contrast evaluation for the backscattering polarimetric images of different targets in turbid medium

Novikova¹,

Bénière²,

Goudail³

et al. 2009

Opt. Express

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It is known that polarization-sensitive backscattering images of different objects in turbid media may show better contrasts than usual intensity images. Polarimetric image contrast depends on both target and background polarization properties and typically involves averaging over groups of pixels, corresponding to given areas of the image. By means of numerical modelling we show that the experimental arrangement, namely, the shape of turbid medium container, the optical properties of the container walls, the relative positioning of the absorbing, scattering and reflecting targets with respect to each other and to the container walls, as well as the choice of the image areas for the contrast calculations, can strongly affect the final results for both linearly and circularly polarized light.

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Section: Introductionmentioning

confidence: 99%

“…As follows from Eq. (1),(3) and(8) the OSC values for linearly and circularly polarized light can be expressed in terms of Mueller matrix coefficients:…”

mentioning

confidence: 99%

Sources of possible artefacts in the contrast evaluation for the backscattering polarimetric images of different targets in turbid medium

Novikova¹,

Bénière²,

Goudail³

et al. 2009

Opt. Express

View full text Add to dashboard Cite

show abstract

“…Once the polarization state is discriminated by the polarimeter instruments, the unscattered light is separated from the scattered light. Image resolution and object recognition are improved by extracting the unscattered or weakly scattered light (Giakos et al, 2004;Miasnikov & Kondranin, 1992;Tonebon S. & Reuter R., 2000).…”

Section: Polarizationmentioning

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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