BRDF Measurement Modelling using Wavelets for Efficient Path Tracing

Claustres, Luc; Paulin, Mathias; Boucher, Yann

doi:10.1111/j.1467-8659..00718.x

Cited by 22 publications

(25 citation statements)

References 27 publications

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“…This example illustrates that the whole radiometric information is useful to perform an accurate physical simulation. We have already shown that a better compression, according to modelling error, can be reached with our approach compared to the work of Lalonde at fixed wavelength [9]. Table 3 also demonstrates that our adaptive generic compression scheme significantly improve spectral modelling at high compression rates compared to the results we have presented in [9].…”

Section: Brdfssupporting

confidence: 55%

“…We have already shown that a better compression, according to modelling error, can be reached with our approach compared to the work of Lalonde at fixed wavelength [9]. Table 3 also demonstrates that our adaptive generic compression scheme significantly improve spectral modelling at high compression rates compared to the results we have presented in [9]. For instance the relative L 2 error has been respectively reduced by 34%, 70%, and 46% for the spectralon, plywood and plastic BRDFs in the case of the 128:1 compression ra- tio.…”

Section: Brdfsmentioning

confidence: 91%

“…In this paper, we extend our previous work on waveletbased BRDF modelling [9]. First by achieving better compression, providing the function's domain with a uniform accuracy, thanks to an automatic adaptive scheme that computes a local threshold for each space of the decomposition (see section 4.2 and 5.2.1).…”

mentioning

confidence: 94%

“…We have presented in [9] an importance sampling method based on the wavelet representation of the BRDF. Reflected directions are generated according to the BRDF magnitude in a O(log 4 n) time complexity, where n is the number of spherical triangles.…”

Section: Importance Samplingmentioning

confidence: 99%

“…The selection strategy is to pick, for a given compression ratio, the best basis in terms of global error. Basic structures to manage sparse data are detailed in [9].…”

Section: Wavelet-based Radiometry Frameworkmentioning

confidence: 99%

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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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Section: Brdfssupporting

confidence: 55%

Section: Brdfsmentioning

confidence: 91%

mentioning

confidence: 94%

Section: Importance Samplingmentioning

confidence: 99%

“…The selection strategy is to pick, for a given compression ratio, the best basis in terms of global error. Basic structures to manage sparse data are detailed in [9].…”

Section: Wavelet-based Radiometry Frameworkmentioning

confidence: 99%

See 3 more Smart Citations