Robust light transport simulation via metropolised bidirectional estimators

Self Cite

Monte Carlo methods for physically‐based light transport simulation are broadly adopted in the feature film production, animation and visual effects industries. These methods, however, often result in noisy images and have slow convergence. As such, improving the convergence of Monte Carlo rendering remains an important open problem. Gradient‐domain light transport is a recent family of techniques that can accelerate Monte Carlo rendering by up to an order of magnitude, leveraging a gradient‐based estimation and a reformulation of the rendering problem as an image reconstruction. This state of the art report comprehensively frames the fundamentals of gradient‐domain rendering, as well as the pragmatic details behind practical gradient‐domain uniand bidirectional path tracing and photon density estimation algorithms. Moreover, we discuss the various image reconstruction schemes that are crucial to accurate and stable gradient‐domain rendering. Finally, we benchmark various gradient‐domain techniques against the state‐of‐the‐art in denoising methods before discussing open problems.

Section: More Advanced Algorithmsmentioning

confidence: 99%

A Survey on Gradient‐Domain Rendering

Hua

Gruson

Petitjean

et al. 2019

Self Cite

“…The first such rendering method was Metropolis Light Transport [VG97]. Since then a number of improvements were made, including the combination of MLT and VCM by Šik et al [ŠOHK16]. More about MCMC in general can be found in a recent survey from Šik and Krivánek [ŠK18].…”

Section: Related Workmentioning

confidence: 99%

Microfacet Model Regularization for Robust Light Transport

Jendersie

Grosch

2019

Today, Monte Carlo light transport algorithms are used in many applications to render realistic images. Depending on the complexity of the used methods, several light effects can or cannot be found by the sampling process. Especially, specular and smooth glossy surfaces often lead to high noise and missing light effects. Path space regularization provides a solution, improving any sampling algorithm, by modifying the material evaluation code. Previously, Kaplanyan and Dachsbacher [KD13] introduced the concept for pure specular interactions. We extend this idea to the commonly used microfacet models by manipulating the roughness parameter prior to the evaluation. We also show that this kind of regularization requires a change in the MIS weight computation and provide the solution. Finally, we propose two heuristics to adaptively reduce the introduced bias. Using our method, many complex light effects are reproduced and the fidelity of smooth objects is increased. Additionally, if a path was sampleable before, the variance is partially reduced.

“…In this setting, it could also be interesting to use our usefulness measure with a Metropolis approach. For instance, the binary visibility and contribution target functions used by Šik et al [ŠOHK16] could additionally apply our usefulness threshold, to focus on useful photons. Support for volumetric caustics should also be possible with these approaches.…”

Section: Limitations and Future Workmentioning

confidence: 99%

“…Metropolised VCM [ŠOHK16] distributes photons according to their MIS weighted image contribution. That improves efficiency by tracing fewer photons with low MIS weights.…”

Section: Related Workmentioning

confidence: 99%

“…Difficult specular transport can be rendered with Markov chain approaches using regularization [KD13] or manifold exploration [JM12]. The Metropolis algorithm can also be used in conjunction with Photon mapping [ŠOHK16,GRŠ*17,HJ11], so as to distribute photons according to visibility, image contribution, or in a way that ensures a uniform error distribution. However, all these methods suffer from the drawbacks common to MCMC approaches.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Efficient Caustic Rendering with Lightweight Photon Mapping

Grittmann

Pérard-Gayot

Slusallek

et al. 2018

Self Cite

Robust and efficient rendering of complex lighting effects, such as caustics, remains a challenging task. While algorithms like vertex connection and merging can render such effects robustly, their significant overhead over a simple path tracer is not always justified and – as we show in this paper ‐ also not necessary. In current rendering solutions, caustics often require the user to enable a specialized algorithm, usually a photon mapper, and hand‐tune its parameters. But even with carefully chosen parameters, photon mapping may still trace many photons that the path tracer could sample well enough, or, even worse, that are not visible at all. Our goal is robust, yet lightweight, caustics rendering. To that end, we propose a technique to identify and focus computation on the photon paths that offer significant variance reduction over samples from a path tracer. We apply this technique in a rendering solution combining path tracing and photon mapping. The photon emission is automatically guided towards regions where the photons are useful, i.e., provide substantial variance reduction for the currently rendered image. Our method achieves better photon densities with fewer light paths (and thus photons) than emission guiding approaches based on visual importance. In addition, we automatically determine an appropriate number of photons for a given scene, and the algorithm gracefully degenerates to pure path tracing for scenes that do not benefit from photon mapping.