Monte Carlo method to model optical coherence propagation in random media

Shen, Zhean; Sukhov, Sergey; Dogariu, Aristide

doi:10.1364/josaa.34.002189

Cited by 16 publications

(9 citation statements)

References 32 publications

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“…Given the geometry of the scene, the ambient light that reaches the detector will necessarily result from diffuse scattering (i.e., specularly reflected ambient light from secondary sources will not reach the detector due to unequal angles of incidence and reflection). Because there is a Fourier transform relationship between scattered photon angle and coherence (see Appendix B for more details), the large angle diffuse spread in the ambient light introduces a narrow peak in the coherence function at ρ = 0 [33], [35]. Recalling the relationship between intensity and coherence I(r) = W (r, 0), we can see that the peak exactly coincides with the intensity measurements.…”

Section: B Coherence Measurementssupporting

confidence: 53%

“…example plot of such a coherence sample is shown in Fig. 2 For the interaction with the wall, the angular spread of photons can be assumed to be governed by a Gaussian function [15], [33]. The standard deviation of the angular spread along the x and y axes is w = (w x , w y ).…”

Section: Physical Modelmentioning

confidence: 99%

“…Here, θ = (θ x , θ y ) is the angle between the surface normal and the incident vector along the x and y axes, while θ is the reflected angle defined in a similar way. The link between coherence and the angular spread of the light (in this context referred to as specific intensity) is via the relation [33], [46]…”

Section: Appendix B Coherence Derivationsmentioning

confidence: 99%

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Multi-Modal Non-Line-of-Sight Passive Imaging

Beckus

Tamasan

Atia

2019

IEEE Trans. on Image Process.

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We consider the non-line-of-sight (NLOS) imaging of an object using the light reflected off a diffusive wall. The wall scatters incident light such that a lens is no longer useful to form an image. Instead, we exploit the 4D spatial coherence function to reconstruct a 2D projection of the obscured object. The approach is completely passive in the sense that no control over the light illuminating the object is assumed and is compatible with the partially coherent fields ubiquitous in both the indoor and outdoor environments. We formulate a multi-criteria convex optimization problem for reconstruction, which fuses the reflected field's intensity and spatial coherence information at different scales. Our formulation leverages established optics models of light propagation and scattering and exploits the sparsity common to many images in different bases. We also develop an algorithm based on the alternating direction method of multipliers to efficiently solve the convex program proposed. A means for analyzing the null space of the measurement matrices is provided as well as a means for weighting the contribution of individual measurements to the reconstruction. This paper holds promise to advance passive imaging in the challenging NLOS regimes in which the intensity does not necessarily retain distinguishable features and provides a framework for multimodal information fusion for efficient scene reconstruction.

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Section: B Coherence Measurementssupporting

confidence: 53%

Section: Physical Modelmentioning

confidence: 99%

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Multi-Modal Non-Line-of-Sight Passive Imaging

Beckus

Tamasan

Atia

2019

IEEE Trans. on Image Process.

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“…ere have been a empts to use Monte Carlo algorithms to evaluate various properties of coherence and partial coherence of light a er propagating through a sca ering tissue (Pierrat et al 2005;Shen et al 2017). O en these are based on using the radiative transfer equation (RTE) and intensity-based Monte Carlo rendering, then applying a Fourier transform on its result.…”

Section: Related Workmentioning

confidence: 99%

A Monte Carlo framework for rendering speckle statistics in scattering media

et al. 2019

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“…Where the beam ( , ) enters ( > 0), leaves ( < 0)) or is coplanar to ( = 0)) the surface of the triangle with vertices ( , ), ( , ), ( , ). This approach can be used to coherence propagation [8].…”

Section: Scattering and Green's Functions Theoretical Modelmentioning

confidence: 99%

Light propagation in highly scattering biological tissues analyzed by Green's functions

Fanjul-Vélez¹,

Arce-Diego²,

Ganoza-Quintana³

2019

Optical Interactions With Tissue and Cells XXX

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Biomedical optical techniques of treatment, characterization and surgery are strongly dependent on light propagation in tissues. Information that goes beyond pure intensity, such as polarization or other coherence parameters, can provide increased contrast. This contrast is critical in clinical applications, as malignant tissue has to be distinguished from healthy one, or a particular component or structure has to be highlighted and detected. The appropriate consideration of these further light-tissue interaction properties requires taking into account phase and coherence. The complexity of the problem increases as biological tissues present usually high scattering. This fact greatly influences optical propagation, and is usually a fundamental limitation in optical diagnostic techniques. Light propagation in static scattering media can be analyzed by Green's functions. Electromagnetic propagation could be then considered, including coherence phenomena. However, analytical solutions are complex and require usually numerical methods to obtain a result. Monte Carlo approaches are particularly well-suited in biological tissues. In this work light propagation in highly scattering biological tissues is analyzed first by Green's functions. The limited geometry of this analytical approach serves as a first approach for more complex structures. More realistic biological tissue models are proposed and solved via a threedimensional time-resolved Monte Carlo approach. The model is applied to dermatological tumoral tissues. The results of scattering by Green's functions and the Monte Carlo approach are compared, and the potential contrast of coherence parameters is analyzed in diagnostic applications.

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Monte Carlo method to model optical coherence propagation in random media

Cited by 16 publications

References 32 publications

Multi-Modal Non-Line-of-Sight Passive Imaging

Multi-Modal Non-Line-of-Sight Passive Imaging

A Monte Carlo framework for rendering speckle statistics in scattering media

Light propagation in highly scattering biological tissues analyzed by Green's functions

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