Rendering natural waters taking fluorescence into account

Cerezo, Eva; Serón, Francisco J.

doi:10.1002/cav.10

Cited by 7 publications

(8 citation statements)

References 14 publications

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“…An extensive discussion of this term was presented later by Cerezo et al . [ 27 , 28 ] and Gutierrez et al . [ 29 , 30 ] to simulate the inelastic scattering of ocean waters.…”

Section: Methods (Lsfm Modeling)mentioning

confidence: 99%

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Physically-based in silico light sheet microscopy for visualizing fluorescent brain models

et al. 2015

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BackgroundWe present a physically-based computational model of the light sheet fluorescence microscope (LSFM). Based on Monte Carlo ray tracing and geometric optics, our method simulates the operational aspects and image formation process of the LSFM. This simulated, in silico LSFM creates synthetic images of digital fluorescent specimens that can resemble those generated by a real LSFM, as opposed to established visualization methods producing visually-plausible images. We also propose an accurate fluorescence rendering model which takes into account the intrinsic characteristics of fluorescent dyes to simulate the light interaction with fluorescent biological specimen.ResultsWe demonstrate first results of our visualization pipeline to a simplified brain tissue model reconstructed from the somatosensory cortex of a young rat. The modeling aspects of the LSFM units are qualitatively analysed, and the results of the fluorescence model were quantitatively validated against the fluorescence brightness equation and characteristic emission spectra of different fluorescent dyes.AMS subject classificationModelling and simulation

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“…An extensive discussion of this term was presented later by Cerezo et al . [ 27 , 28 ] and Gutierrez et al . [ 29 , 30 ] to simulate the inelastic scattering of ocean waters.…”

Section: Methods (Lsfm Modeling)mentioning

confidence: 99%

“…Cerezo et al . [ 27 , 28 ] and Gutierrez et al . [ 29 , 30 ] developed further extensions to Glassner's model to account for these properties for the purpose of rendering the fluorescent pigments in the ocean.…”

Section: Introductionmentioning

confidence: 99%

Physically-based in silico light sheet microscopy for visualizing fluorescent brain models

et al. 2015

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“…Subsurface scattering was also addressed by several authors [PA00, CS04] by taking into account several bio‐optical parameters such as chlorophyll concentration and turbidity [Jer76]. In that case, coefficients for attenuation a (λ) and diffusion b (λ) are obtained from physical laws [Mor91, GM83] according to the phytoplankton concentration C p inside water:…”

Section: Realistic Ocean Surface Rendering and Lightingmentioning

confidence: 99%

A Survey of Ocean Simulation and Rendering Techniques in Computer Graphics

Darles

Crespin

Ghazanfarpour

et al. 2010

Computer Graphics Forum

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International audienceThis paper presents a survey of ocean simulation and rendering methods in computer graphics. To model and animate the ocean's surface, these methods mainly rely on two main approaches: on the one hand, those which approximate ocean dynamics with parametric, spectral or hybrid models and use empirical laws from oceanographic research. We will see that this type of methods essentially allows the simulation of ocean scenes in the deep water domain, without breaking waves. On the other hand, physically-based methods use Navier-Stokes Equations (NSE) to represent breaking waves and more generally ocean surface near the shore. We also describe ocean rendering methods in computer graphics, with a special interest in the simulation of phenomena such as foam and spray, and light's interaction with the ocean surface

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“…Recently, the Lorenz-Mie theory has been generalized and applied to rendering natural waters by Frisvad, Christensen and Jensen [FCJ07], also neglecting the effects of inelastic scattering. Cerezo and Seron [CS04] also develop a bio-optical model. Whilst the goal of their work is closely related to ours, we overcome here significant shortcomings:…”

Section: Related Workmentioning

confidence: 99%