Error-bound wavelength selection for spectral rendering

Zéghers, Eric; Carré, Stéphane; Bouatouch, Kadi

doi:10.1007/s003710050115

Cited by 7 publications

(4 citation statements)

References 3 publications

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“…Result precision, memory usage and rendering time are directly related to the number of samples [Hal99] [JF99] – but also to the properties of the input data, and to some degree also on which physical effects one supports in a given system. So a main research area was how to find a good number and distribution of samples [CW05, ZCB97, WTP00] – albeit with inconclusive results so far.…”

Section: State Of the Art And Backgroundmentioning

confidence: 99%

Hero Wavelength Spectral Sampling

Wilkie

Nawaz²,

Droske³

et al. 2014

Computer Graphics Forum

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Figure 1: Wavelength-dependent subsurface scattering with single wavelength sampling (left) and our proposed method (right). The lower image halves are rendered with 4 paths per pixel, and the upper halves are rendered with 1024. For both sample counts, the hero wavelength images took only 3.5% longer than the single wavelength ones. AbstractWe present a spectral rendering technique that offers a compelling set of advantages over existing approaches.The key idea is to propagate energy along paths for a small, constant number of changing wavelengths. The first of these, the hero wavelength, is randomly sampled for each path, and all directional sampling is solely based on it. The additional wavelengths are placed at equal distances from the hero wavelength, so that all path wavelengths together always evenly cover the visible range. A related technique, spectral multiple importance sampling, was already introduced a few years ago. We propose a simplified and optimised version of this approach which is easier to implement, has good performance characteristics, and is actually more powerful than the original method. Our proposed method is also superior to techniques which use a static spectral representation, as it does not suffer from any inherent representation bias. We demonstrate the performance of our method in several application areas that are of critical importance for production work, such as fidelity of colour reproduction, sub-surface scattering, dispersion and volumetric effects. We also discuss how to couple our proposed approach with several technologies that are important in current production systems, such as photon maps, bidirectional path tracing, environment maps, and participating media.

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Section: State Of the Art And Backgroundmentioning

confidence: 99%

Hero Wavelength Spectral Sampling

Wilkie

Nawaz²,

Droske³

et al. 2014

Computer Graphics Forum

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“…Another approach is to minimize the spectral information by simplifying it while keeping the error to a minimum. For example, Zeghers et al suppress/simplify spectral information over nearby wavelengths by connecting their two suppressed local peaks [35], Iehl and Perochè [36] represent a range of wavelengths as a constant value.…”

Section: Related Workmentioning

confidence: 99%

Spectral caustic rendering of a homogeneous caustic object based on wavelength clustering and eye sensitivity

et al. 2014

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In the real world, the index of refraction of a refractive object (caustic object) varies across the wavelengths. Therefore, in physically based caustic rendering, we need to take into account spectral information. However, this may lead to prohibitive running time. In response, we propose a two-step acceleration scheme for spectral caustic rendering. Our acceleration scheme takes into account information across visible wavelengths of the scene, that is, the index of refraction (IOR) (caustic object), light power (light), and material reflectance (surface). To process visible wavelengths effectively, firstly we cluster the wavelengths which have similar first refraction (air to caustic object) directions. In this way, all the wavelengths in a cluster can be represented by one light ray during rendering. Secondly, by considering the surrounding objects (their material reflectance from and visible surface area of the caustic objects) and light power, we compute the refinement amount of each wavelength cluster. Our accelerated algorithm can produce photorealistic rendering results close to their reference images (which are generated by rendering every 1 nm of visible wavelengths) with a significant acceleration magnitude. Computational experiment results and comparative analyses are reported in the paper

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“…Relevant wavelength selection in the context of spectral rendering has also been studied [76,42]. A method based on the Haar wavelet decomposition proposes an adaptive representation of spectral data with a control of the perceptual error [23,58].…”

Section: Separable Decompositionsmentioning

confidence: 99%

A wavelet-based framework for acquired radiometric quantity representation and accurate physical rendering

2006

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In this paper, we present a framework based on a generic representation, which is able to handle most of the radiometric quantities required by global illumination softwares. A sparse representation in the wavelet space is built using the separation between the directional and the wavelength dependence of such radiometric quantities. Particularly, we show how to use this representation for spectral power distribution, spectral reflectance and phase function measurements modelling. Then, we explain how the representation is useful to perform spectral rendering. On one hand, it speeds up spectral path tracing by importance sampling to generate reflected directions and by avoiding expensive computations usually done on the fly. On the other hand, it allows efficient spectral photon mapping, both in terms of memory and speed. We also show how complex light emission from real luminaires can be efficiently sampled to emit photons with our numerical model.

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Error-bound wavelength selection for spectral rendering

Cited by 7 publications

References 3 publications

Hero Wavelength Spectral Sampling

Hero Wavelength Spectral Sampling

Spectral caustic rendering of a homogeneous caustic object based on wavelength clustering and eye sensitivity

A wavelet-based framework for acquired radiometric quantity representation and accurate physical rendering

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