Monte Carlo Light Transport Simulation Research Articles

A Hyperspectral Space of Skin Tones for Inverse Rendering of Biophysical Skin Properties

AbstractWe present a method for estimating the main properties of human skin, leveraging a hyperspectral dataset of skin tones synthetically generated through a biophysical layered skin model and Monte Carlo light transport simulations. Our approach learns the mapping between the skin parameters and diffuse skin reflectance in such space through an encoder‐decoder network. We assess the performance of RGB and spectral reflectance up to 1 μm, allowing the model to retrieve visible and near‐infrared. Instead of restricting the parameters to values in the ranges reported in medical literature, we allow the model to exceed such ranges to gain expressiveness to recover outliers like beard, eyebrows, rushes and other imperfections. The continuity of our albedo space allows to recover smooth textures of skin properties, enabling reflectance manipulations by meaningful edits of the skin properties. The space is robust under different illumination conditions, and presents high spectral similarity with the current largest datasets of spectral measurements of real human skin while expanding its gamut.

Correlation‐Aware Multiple Importance Sampling for Bidirectional Rendering Algorithms

AbstractCombining diverse sampling techniques via multiple importance sampling (MIS) is key to achieving robustness in modern Monte Carlo light transport simulation. Many such methods additionally employ correlated path sampling to boost efficiency. Photon mapping, bidirectional path tracing, and path‐reuse algorithms construct sets of paths that share a common prefix. This correlation is ignored by classical MIS heuristics, which can result in poor technique combination and noisy images. We propose a practical and robust solution to that problem. Our idea is to incorporate correlation knowledge into the balance heuristic, based on known path densities that are already required for MIS. This correlation‐aware heuristic can achieve considerably lower error than the balance heuristic, while avoiding computational and memory overhead.

Neural Acceleration of Scattering‐Aware Color 3D Printing

AbstractWith the wider availability of full‐color 3D printers, color‐accurate 3D‐print preparation has received increased attention. A key challenge lies in the inherent translucency of commonly used print materials that blurs out details of the color texture. Previous work tries to compensate for these scattering effects through strategic assignment of colored primary materials to printer voxels. To date, the highest‐quality approach uses iterative optimization that relies on computationally expensive Monte Carlo light transport simulation to predict the surface appearance from subsurface scattering within a given print material distribution; that optimization, however, takes in the order of days on a single machine. In our work, we dramatically speed up the process by replacing the light transport simulation with a data‐driven approach. Leveraging a deep neural network to predict the scattering within a highly heterogeneous medium, our method performs around two orders of magnitude faster than Monte Carlo rendering while yielding optimization results of similar quality level. The network is based on an established method from atmospheric cloud rendering, adapted to our domain and extended by a physically motivated weight sharing scheme that substantially reduces the network size. We analyze its performance in an end‐to‐end print preparation pipeline and compare quality and runtime to alternative approaches, and demonstrate its generalization to unseen geometry and material values. This for the first time enables full heterogenous material optimization for 3D‐print preparation within time frames in the order of the actual printing time.

Slope-space integrals for specular next event estimation

Monte Carlo light transport simulations often lack robustness in scenes containing specular or near-specular materials. Widely used uni- and bidirectional sampling strategies tend to find light paths involving such materials with insufficient probability, producing unusable images that are contaminated by significant variance. This article addresses the problem of sampling a light path connecting two given scene points via a single specular reflection or refraction, extending the range of scenes that can be robustly handled by unbiased path sampling techniques. Our technique enables efficient rendering of challenging transport phenomena caused by such paths, such as underwater caustics or caustics involving glossy metallic objects. We derive analytic expressions that predict the total radiance due to a single reflective or refractive triangle with a microfacet BSDF and we show that this reduces to the well known Lambert boundary integral for irradiance. We subsequently show how this can be leveraged to efficiently sample connections on meshes comprised of vast numbers of triangles. Our derivation builds on the theory of off-center microfacets and involves integrals in the space of surface slopes. Our approach straightforwardly applies to the related problem of rendering glints with high-resolution normal maps describing specular microstructure. Our formulation alleviates problems raised by singularities in filtering integrals and enables a generalization of previous work to perfectly specular materials. We also extend previous work to the case of GGX distributions and introduce new techniques to improve accuracy and performance.

Experimental validation of a spectroscopic Monte Carlo light transport simulation technique and Raman scattering depth sensing analysis in biological tissue.

.Significance: Raman spectroscopy (RS) applied to surgical guidance is attracting attention among scientists in biomedical optics. Offering a computational platform for studying depth-resolved RS and probing molecular specificity of different tissue layers is of crucial importance to increase the precision of these techniques and facilitate their clinical adoption.Aim: The aim of this work was to present a rigorous analysis of inelastic scattering depth sampling and elucidate the relationship between sensing depth of the Raman effect and optical properties of the tissue under interrogation.Approach: A new Monte Carlo (MC) package was developed to simulate absorption, fluorescence, elastic, and inelastic scattering of light in tissue. The validity of the MC algorithm was demonstrated by comparison with experimental Raman spectra in phantoms of known optical properties using nylon and polydimethylsiloxane as Raman-active compounds. A series of MC simulations were performed to study the effects of optical properties on Raman sensing depth for an imaging geometry consistent with single-point detection using a handheld fiber optics probe system.Results: The MC code was used to estimate the Raman sensing depth of a handheld fiber optics system. For absorption and reduced scattering coefficients of 0.001 and , the sensing depth varied from 105 to for a range of Raman probabilities from to . Further, for a realistic Raman probability of , the sensing depth ranged between 10 and for the range of absorption coefficients 0.001 to and reduced scattering coefficients of 0.5 to .Conclusions: A spectroscopic MC light transport simulation platform was developed and validated against experimental measurements in tissue phantoms and used to predict depth sensing in tissue. It is hoped that the current package and reported results provide the research community with an effective simulating tool to improve the development of clinical applications of RS.

Selectively metropolised Monte Carlo light transport simulation

Light transport is a complex problem with many solutions. Practitioners are now faced with the difficult task of choosing which rendering algorithm to use for any given scene. Simple Monte Carlo methods, such as path tracing, work well for the majority of lighting scenarios, but introduce excessive variance when they encounter transport they cannot sample (such as caustics). More sophisticated rendering algorithms, such as bidirectional path tracing, handle a larger class of light transport robustly, but have a high computational overhead that makes them inefficient for scenes that are not dominated by difficult transport. The underlying problem is that rendering algorithms can only be executed indiscriminately on all transport, even though they may only offer improvement for a subset of paths. In this paper, we introduce a new scheme for selectively combining different Monte Carlo rendering algorithms. We use a simple transport method (e.g. path tracing) as the base, and treat high variance "fireflies" as seeds for a Markov chain that locally uses a Metropolised version of a more sophisticated transport method for exploration, removing the firefly in an unbiased manner. We use a weighting scheme inspired by multiple importance sampling to partition the integrand into regions the base method can sample well and those it cannot, and only use Metropolis for the latter. This constrains the Markov chain to paths where it offers improvement, and keeps it away from regions already handled well by the base estimator. Combined with stratified initialization, short chain lengths and careful allocation of samples, this vastly reduces non-uniform noise and temporal flickering artifacts normally encountered with a global application of Metropolis methods. Through careful design choices, we ensure our algorithm never performs much worse than the base estimator alone, and usually performs significantly better, thereby reducing the need to experiment with different algorithms for each scene.

Manifold Next Event Estimation

AbstractWe present manifold next event estimation (MNEE), a specialised technique for Monte Carlo light transport simulation to render refractive caustics by connecting surfaces to light sources (next event estimation) across transmissive interfaces. We employ correlated sampling by means of a perturbation strategy to explore all half vectors in the case of rough transmission while remaining outside of the context of Markov chain Monte Carlo, improving temporal stability. MNEE builds on differential geometry and manifold walks. It is very lightweight in its memory requirements, as it does not use light caching methods such as photon maps or importance sampling records. The method integrates seamlessly with existing Monte Carlo estimators via multiple importance sampling.

Path-space Motion Estimation and Decomposition for Robust Animation Filtering

Renderings of animation sequences with physics-based Monte Carlo light transport simulations are exceedingly costly to generate frame-by-frame, yet much of this computation is highly redundant due ...

Path‐space Motion Estimation and Decomposition for Robust Animation Filtering

AbstractRenderings of animation sequences with physics‐based Monte Carlo light transport simulations are exceedingly costly to generate frame‐by‐frame, yet much of this computation is highly redundant due to the strong coherence in space, time and among samples. A promising approach pursued in prior work entails subsampling the sequence in space, time, and number of samples, followed by image‐based spatio‐temporal upsampling and denoising. These methods can provide significant performance gains, though major issues remain: firstly, in a multiple scattering simulation, the final pixel color is the composite of many different light transport phenomena, and this conflicting information causes artifacts in image‐based methods. Secondly, motion vectors are needed to establish correspondence between the pixels in different frames, but it is unclear how to obtain them for most kinds of light paths (e.g. an object seen through a curved glass panel).To reduce these ambiguities, we propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths. Each component is accompanied by motion vectors and other auxiliary features such as reflectance and surface normals. The motion vectors of specular paths are computed using a temporal extension of manifold exploration and the remaining components use a specialized variant of optical flow. Our experiments show that this decomposition leads to significant improvements in three image‐based applications: denoising, spatial upsampling, and temporal interpolation.

Manifold Next Event Estimation

We present manifold next event estimation MNEE, a specialised technique for Monte Carlo light transport simulation to render refractive caustics by connecting surfaces to light sources next event e...

Predicting the timing properties of phosphor-coated scintillators using Monte Carlo light transport simulation

Current developments in positron emission tomography focus on improving timing performance for scanners with time-of-flight (TOF) capability, and incorporating depth-of-interaction (DOI) information. Recent studies have shown that incorporating DOI correction in TOF detectors can improve timing resolution, and that DOI also becomes more important in long axial field-of-view scanners. We have previously reported the development of DOI-encoding detectors using phosphor-coated scintillation crystals; here we study the timing properties of those crystals to assess the feasibility of providing some level of DOI information without significantly degrading the timing performance. We used Monte Carlo simulations to provide a detailed understanding of light transport in phosphor-coated crystals which cannot be fully characterized experimentally. Our simulations used a custom reflectance model based on 3D crystal surface measurements. Lutetium oxyorthosilicate crystals were simulated with a phosphor coating in contact with the scintillator surfaces and an external diffuse reflector (teflon). Light output, energy resolution, and pulse shape showed excellent agreement with experimental data obtained on 3 × 3 × 10 mm3 crystals coupled to a photomultiplier tube. Scintillator intrinsic timing resolution was simulated with head-on and side-on configurations, confirming the trends observed experimentally. These results indicate that the model may be used to predict timing properties in phosphor-coated crystals and guide the coating for optimal DOI resolution/timing performance trade-off for a given crystal geometry. Simulation data suggested that a time stamp generated from early photoelectrons minimizes degradation of the timing resolution, thus making this method potentially more useful for TOF-DOI detectors than our initial experiments suggested. Finally, this approach could easily be extended to the study of timing properties in other scintillation crystals, with a range of treatments and materials attached to the surface.

3D Millimeter Event Localization in Bulk Scintillator Crystals

One of the primary goals of scintillator-based gamma-ray detector development is to obtain spatial resolutions in bulk crystals at the millimeter level in all three spatial dimensions. An even more challenging goal is to disentangle multiple simultaneous energy depositions with comparable spatial resolutions. We are exploring a new technique to achieve this level of performance through the use of close-coupled, coded-aperture shadow masks placed between the crystal and a position-sensitive phototransducer. We report on simulations of such a device using Monte Carlo light transport simulations performed with GEANT 4. Initial indications are promising; however, the technique will require a very high level of performance from the phototransducer.

Light transport simulation with vertex connection and merging

Developing robust light transport simulation algorithms that are capable of dealing with arbitrary input scenes remains an elusive challenge. Although efficient global illumination algorithms exist, an acceptable approximation error in a reasonable amount of time is usually only achieved for specific types of input scenes. To address this problem, we present a reformulation of photon mapping as a bidirectional path sampling technique for Monte Carlo light transport simulation. The benefit of our new formulation is twofold. First, it makes it possible, for the first time, to explain in a formal manner the relative efficiency of photon mapping and bidirectional path tracing, which have so far been considered conceptually incompatible solutions to the light transport problem. Second, it allows for a seamless integration of the two methods into a more robust combined rendering algorithm via multiple importance sampling. A progressive version of this algorithm is consistent and efficiently handles a wide variety of lighting conditions, ranging from direct illumination, diffuse and glossy inter-reflections, to specular-diffuse-specular light transport. Our analysis shows that this algorithm inherits the high asymptotic performance from bidirectional path tracing for most light path types, while benefiting from the efficiency of photon mapping for specular-diffuse-specular lighting effects.

Lubberts effect in columnar phosphors

Noise transfer in granular x-ray imaging phosphor screens is not proportional to the square of the magnitude of the signal transfer when the transfer properties are considered for the entire screen thickness, unless appropriately weighted at each depth of interaction. This property, known as the Lubberts effect, has not yet been studied in columnar structured screens because of a lack of a generalized description of the depth-dependent light transport. In this paper, we investigate the signal and noise transfer characteristics of columnar phosphors used in digital mammography detectors using DETECT-II, an optical Monte Carlo light transport simulation code. We first validate our choice of optical parameters for the description of granular and columnar screens using published normalized modulation transfer (MTF) experimental data. Our calculations of MTF match empirically measured MTFs for a granular film/screen analog system, and for an indirect x-ray digital imaging system with CsI:Tl screen representative of digital mammography systems. Using the depth-dependent spread functions and collection efficiencies, we calculate the signal and noise transfer functions and the Lubberts fraction, which is the ratio of the signal transfer function to the noise transfer function, for different screen thicknesses of granular and columnar phosphors. We find that the Lubberts fraction of a 85 microm granular screen model corresponding to a Gd2O2S:Tb screen is similar to the fraction for a 100 microm columnar CsI:Tl screen.

Image quality degradation by light scattering processes in high performance display devices for medical imaging

This thesis addresses the characterization of light scattering processes that degrade image quality in high performance electronic display devices for radiography. Using novel experimental and computational tools, we study the lateral diffusion of light in emissive displays that causes extensive veiling glare and significant reduction of the contrast. In addition, we examine the deleterious effects of ambient light reflections that affect the contrast of low luminance regions, and superimpose unwanted structured signal. To model veiling glare and display reflections, we use a Monte Carlo light transport simulation code, DETECT‐II, that tracks individual photons through multiple scattering events. The simulation accounts for the photon polarization state, and provides descriptions for rough surfaces and thin film coatings. A new experimental method to measure veiling glare is described based on a conic collimated probe that minimizes unwanted contributions from bright areas. We show that veiling glare ratios in the order of a few hundreds can be measured with an uncertainty of a few percent. For a high performance medical imaging monitor with anti‐reflective coating, the veiling glare ratio for a 1 cm diameter dark spot was measured to be 240. Finally, we introduce experimental techniques for measurements of display reflectance, and we compare measured reflection coefficients with Monte Carlo estimates. In spite of having comparable reflection coefficients, the low maximum luminance of current cathode‐ray tube devices worsens the effect of ambient light reflections when compared to radiographic film. Flat panel technologies can perform even better than film due to a thin faceplate, increased light absorption, and high brightness.