Stochastic Iteration for Non‐diffuse Global Illumination

Szirmay‐Kalos, László; Benedek, Balázs

doi:10.1111/1467-8659.00344

Cited by 18 publications

(16 citation statements)

References 37 publications

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“…Parallel ray-bundle tracing transfers the radiance of all patches parallel to a randomly selected global line in each iteration cycle [8]. Bundles carry out surface integration on the fly, thus only the directional integral should be computed.…”

Section: Methods 2: Ray-bundle Shootingmentioning

confidence: 99%

Weighted importance sampling in shooting algorithms

Benedek

Szirmay‐Kalos

György

2003

Proceedings of the 19th Spring Conference on Computer Graphics

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This paper proposes the application of a variance reduction technique called weighted importance sampling in shooting type global illumination algorithms. The sampling applied by shooting type Monte-Carlo global illumination algorithms can mimic the power transfer, but not the BRDFs at the visible target of the transfer. Consequently, these algorithms are poor in rendering visible specular surfaces. In order to eliminate these drawbacks, the BRDFs at the visible targets are taken into account as an additional weighting of the sampling density. After discussing the basic concepts we demonstrate the proposed idea with two algorithms. The first one uses conventional rays, while the second one ray-bundles to transfer the light in the scene.

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Section: Methods 2: Ray-bundle Shootingmentioning

confidence: 99%

Weighted importance sampling in shooting algorithms

Benedek

Szirmay‐Kalos

György

2003

Proceedings of the 19th Spring Conference on Computer Graphics

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“…In the glossy case the radiance is also a function of the direction, which may be handled by applying a similar finite element decomposition in the directional domain [Sillion and Puech 1994], but this approach would increase the storage requirements considerably. Fortunately, applying randomization, we can solve the glossy global illumination problem without introducing any finite elements in the directional domain [Szirmay-Kalos 1999].…”

Section: Introductionmentioning

confidence: 99%

“…The formal basis of such approaches is the stochastic iteration, which was originally proposed for the solution of the linear equations [Neumann 1995;Sbert 1996;Bekaert 1999], then extended for the solution of integral equations [Szirmay-Kalos 1999]. Stochastic iteration means that in the iteration scheme a random transport operator T * f r is used instead of the light-transport operator T f r .…”

Section: Introductionmentioning

confidence: 99%

Stochastic glossy global illumination on the GPU

Barsi¹,

Szirmay‐Kalos²,

Szijártó³

2005

Proceedings of the 21st Spring Conference on Computer Graphics

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This paper presents an algorithm for the glossy global illumination problem, which runs on the Graphics Processing Unit (GPU). In order to meet the architectural limitations of the GPU, we apply randomization in the iteration scheme. Randomization allows to use that set of the possible light interactions, which can be efficiently computed by the GPU, and makes it unnecessary to read back the result to the CPU. Instead of tessellating the surface geometry, the radiance is stored in texture space, and is updated in each iteration. The visibility problem is solved by hardware shadow mapping after hemicube projection. The shooter of the iteration step is selected by a custom mipmapping scheme, realizing approximate importance sampling. The variance is further reduced by partial analytic integration.

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“…Randomization can also help solving this problem as has been proposed by the concept of stochastic iteration [19]. Suppose that we have a random linear operator…”

Section: Introductionmentioning

confidence: 99%

“…This problem, however, can be solved, if the image estimates are computed after each iteration step and the final result is obtained as an average of these estimates [19].…”

Section: Introductionmentioning

confidence: 99%

Hemicube shooting for non-diffuse global illumination

György

Szirmay‐Kalos

Csonka

2002

Proceedings of the 18th Spring Conference on Computer Graphics

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The hemicube is a classical tool to transfer the light power in diffuse radiosity algorithms. The main advantage of the hemicube based light transfer is that the visible patches can easily be identified by the graphics hardware. This paper extends the hemicube approach to solve the nondiffuse global illumination problem. In order to get rid of the quadratic complexity of classical radiosity algorithms and to allow specular surfaces without storing directional finite-elements, the original iteration is replaced by stochastic iteration. Unlike classical iteration where all patches should be selected to gather the radiosity or to shoot their unshot radiosity, stochastic iteration can exploit that a randomly selected patch may represent its neighbours as well, thus accurate results can be obtained even if just a fraction of patches are selected at all. Since stochastic iteration requires just a random approximation of the patch radiance, it can use just a single variable per patch even if the general, non-diffuse problem is attacked. Random selection, however, may introduce noise that is particularly significant where the source and receiver patches are close. We also propose a solution strategy to eliminate these artifacts. The paper also discusses further improvements by applying constant radiance step and by the randomization of the hemicube.

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Stochastic Iteration for Non‐diffuse Global Illumination

Cited by 18 publications

References 37 publications

Weighted importance sampling in shooting algorithms

Weighted importance sampling in shooting algorithms

Stochastic glossy global illumination on the GPU

Hemicube shooting for non-diffuse global illumination

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