Into the Blue: Better Caustics through Photon Relaxation

Spencer, Ben F.; Jones, Mark W.

doi:10.1111/j.1467-8659.2009.01371.x

Cited by 31 publications

(33 citation statements)

References 31 publications

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“…This is especially helpful for combinations of specular-diffuse-specular surface interactions, such as light sources enclosed in glass. Spencer and Jones use hierarchical photon maps to speed up caustic generation [17], and relax the photon map to reduce variance [18]. Recently, Dammertz et al [4] have introduced a biased progressive method, which also divides path space to allow for specialized algorithms to compute a solution for each subspace, in a similar fashion to our work.…”

Section: Related Workmentioning

confidence: 83%

Mixing Monte Carlo and progressive rendering for improved global illumination

2012

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In this paper, we seek to eliminate the noise caused by caustic paths during progressive Monte Carlo path tracing. We employ a filtering strategy over path space, handling each subspace using specialized derivations of path tracing and progressive photon mapping. Evaluating diffuse paths with path tracing allows the use of sample stratification over both pixels and the image as a whole, whilst sharp detailed caustics are produced using progressive photon mapping. This is an efficient, low noise progressive algorithm with vanishing bias combining the advantages of both Monte Carlo methods, and particle tracing.

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Section: Related Workmentioning

confidence: 83%

Mixing Monte Carlo and progressive rendering for improved global illumination

2012

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“…However, there is one important difference to photon relaxation [SJ09]: we must prevent VPLs from moving off the surfaces (esp. on concave surfaces) or under the surface (esp.…”

Section: Iterative Relaxation Of Vpl Locationsmentioning

confidence: 99%

“…Of course we can stratify light sub-paths or use quasi-random sequences (akin to Keller [Kel97]) when generating VPLs, however, some noise in the distribution remains [SJ09].…”

Section: Iterative Relaxation Of Vpl Locationsmentioning

confidence: 99%

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Rich‐VPLs for Improving the Versatility of Many‐Light Methods

Simon

Hanika

Dachsbacher

2015

Computer Graphics Forum

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Figure 1: The Disco scene with multiple colored light sources and reflected highly-glossy caustics where colors add to white light. Rendered with our new virtual light type "Rich-VPL" (left), standard VPLs (middle left), virtual spherical lights [HKWB09] (VSL, middle right), and path tracing reference (right). All many-light methods use 25k virtual lights; our method introduces an overhead of about 50% (less in more complex scenes) on top of standard VPL rendering, but significantly improves the ability to capture glossy and near-specular light transport. VSL require about 20% additional rendering time on top of standard VPLs due to stochastic sampling. AbstractMany-light methods approximate the light transport in a scene by computing the direct illumination from many virtual point light sources (VPLs), and render low-noise images covering a wide range of performance and quality goals. However, they are very inefficient at representing glossy light transport. This is because a VPL on a glossy surface illuminates a small fraction of the scene only, and a tremendous number of VPLs might be necessary to render acceptable images. In this paper, we introduce Rich-VPLs which, in contrast to standard VPLs, represent a multitude of light paths and thus have a more widespread emission profile on glossy surfaces and in scenes with multiple primary light sources. By this, a single Rich-VPL contributes to larger portions of a scene with negligible additional shading cost. Our second contribution is a placement strategy for (Rich-)VPLs proportional to sensor importance times radiance. Although both Rich-VPLs and improved placement can be used individually, they complement each other ideally and share interim computation. Furthermore, both complement existing manylight methods, e.g. Lightcuts or the Virtual Spherical Lights method, and can improve their efficiency as well as their application for scenes with glossy materials and many primary light sources.

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“…Spencer and Jones [37] proposed, in 2009, to add a photon relaxation step to PM that redistributes the photons before the forward render step and photon density estimates. Photon relaxation permits a smaller kernel to be used in the radiance estimate which reduces the bias, but due to the redistribution a low variance is maintained.…”

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confidence: 99%