Scattering through fluids: speckle size measurement and Monte Carlo simulations close to and into the multiple scattering

Piederrière, Y.; Cariou, J; Guern, Y.; Jeune, Bernard; Brun, Guy Le; Lortrian, J

doi:10.1364/opex.12.000176

Cited by 81 publications

(54 citation statements)

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“…However, for perfectly coherent light the dependence on the random scatterer is almost negligible if the scatterer introduces path differences greater than one wavelength [1]. The mean speckle size, as a very important parameter of the speckle pattern, is of great importance to practical applications, e.g., measurement of the roughness of surfaces [2], detection of the scattering center concentration in a biological fluid [3], the particle aggregation [4] or determination of the optical thickness and the particle size in the scattering media [5]. Nevertheless, this paper is focused on determining the mean speckle size influenced purely by the properties of the light beam.…”

Section: Introductionmentioning

confidence: 99%

“…The mean speckle size of a speckle pattern corresponds to the width of a normalized autocorrelation function r I of intensity I observed in a detection plane (x´, y´) [1], [4], [5]. This paper deals with the calculation of the normalized autocorrelation function r I and the subsequent estimation of the mean speckle sizes α x´ and α y´ in both x´-and y´-axis directions, while two approaches of computation are applied and compared to each other.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Methods for Determination of Mean Speckle Size in Simulated Speckle Pattern

Hamarová

Šmı́d

Horváth

et al. 2014

Measurement Science Review

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This paper deals with computation of mean speckle size in a speckle pattern generated through a numerical simulation of speckle after reflection of a Gaussian beam off a rough object's surface. Within this simulation various speckle patterns are obtained by means of change in a parameter of the Gaussian beam. The mean speckle size is computed through two approaches using both the two-dimensional and the one-dimensional normalized autocorrelation function in intensity. Additionally, we propose a distinct optimization of the determination of the mean speckle size by reduction of intensity values representing detected speckle patterns. Results of the determination of the mean speckle size are compared with theoretical predictions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Methods for Determination of Mean Speckle Size in Simulated Speckle Pattern

Hamarová

Šmı́d

Horváth

et al. 2014

Measurement Science Review

View full text Add to dashboard Cite

show abstract

“…4, the central part of the normalized autocorrelation of the intensity image of the GZ surface is shown. It has been demonstrated [23], that more reliable approach for the speckle size estimation is to evaluate the full width at half maximum of the normalized autocorrelation function, instead of searching for the first fall to zero around the correlation peak.…”

Section: Speckle Size Estimationmentioning

confidence: 99%

Roughness Measurement of Dental Materials

Shulev¹,

Roussev²,

Karpuzov³

et al. 2016

Journal of Theoretical and Applied Mechanics

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Abstract. This paper presents a roughness measurement of zirconia ceramics, widely used for dental applications. Surface roughness variations caused by the most commonly used dental instruments for intraoral grinding and polishing are estimated. The applied technique is simple and utilizes the speckle properties of the scattered laser light. It could be easily implemented even in dental clinic environment. The main criteria for roughness estimation is the average speckle size, which varies with the roughness of zirconia. The algorithm used for the speckle size estimation is based on the normalized autocorrelation approach.

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“…The width of this function provides a reasonable measurement of "the average width" of a speckle 36 and is used in many applications. 16,[42][43][44][45] Nevertheless, from turbid media illuminated in a backscattering configuration, we can consider that there is a complex spatial interplay of single and multiple scattering that leads to complex spatial fluctuations of intensity of the field formed outside of the medium. This results in a complex spatial distribution of the different coherent areas produced in the observation plane, with a superposition of large and small speckles from single and multiple scattering, respectively.…”

Section: Speckle Formationmentioning

confidence: 99%

Noninvasive radiation burn diagnosis using speckle phenomenon with a fractal approach to processing

2010

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Abstract. Radiation burns account for the vast majority of damage by accidental radiation exposure. They are characterized by successive and unpredictable inflammatory bursts that are preceded by a clinically latent postirradiation period. Diagnosis and prognosis of the clinical course of radiation burns have proven to be a difficult task. In a classical clinical setting, no technique can distinguish irradiated versus healthy skin during the clinically latent period, hence development of new tools is required. This work describes a noninvasive technique based on speckle phenomenon, designed to support radiation burn diagnosis and prognosis. Speckle produced by strongly scattering media contains information about their optical properties. The difficulty is to extract significant information from speckle patterns to discriminate between strongly scattering media and to characterize any change. Speckle patterns from irradiated and nonirradiated porcine skins are recorded in vivo several times after radiation exposure. A fractal approach is used in the treatment of speckle patterns. The results show that this technique allows discrimination between healthy and irradiated skin, in particular during the clinically latent period ͑p Ͻ 0.01͒. Parameters extracted from speckle patterns discriminate and vary differently with radiation, which means they represent different information about skin changes.

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Scattering through fluids: speckle size measurement and Monte Carlo simulations close to and into the multiple scattering

Cited by 81 publications

References 0 publications

Methods for Determination of Mean Speckle Size in Simulated Speckle Pattern

Methods for Determination of Mean Speckle Size in Simulated Speckle Pattern

Roughness Measurement of Dental Materials

Noninvasive radiation burn diagnosis using speckle phenomenon with a fractal approach to processing

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