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Applications of Spectral Imaging and Reproduction to Cultural Heritage
Published in Filippo Stanco, Sebastiano Battiato, Giovanni Gallo, Digital Imaging for Cultural Heritage Preservation, 2017
Filippo Stanco, Sebastiano Battiato, Giovanni Gallo
If necessary, the model can be further improved to cope with such phenomena as subsurface light scattering and photoluminescence effects such as fluorescence and phosphorescence. Subsurface light scattering is a mechanism of light transport in which light penetrates the surface of a translucent object, is scattered by interacting with the material, and exits the surface at a different point. The light will generally penetrate the surface and be reflected a number of times at irregular angles inside the material, before passing back out of the material at an angle other than the angle it would have if it had been reflected directly off the surface (see Figure 7.4).
Deep neural network approach for annual luminance simulations
Published in Journal of Building Performance Simulation, 2020
Yue Liu, Alex Colburn, Mehlika Inanici
A light transport model describes how light travels in a scene. In traditional Radiance renderings, a light transport model is computed using a backward ray-tracing technique using scene information such as light sources, geometries, and materials. In this study, A DNN model is used to estimate the light transport model (M) through learning the non-linear relationship between illumination conditions (input I) and the corresponding pixel luminance values (output L). The estimated light transport model (M) allows the scene to be rendered under new lighting conditions. Using this method, generating annual luminance maps is a three-step process that involves: (1) acquiring sparse samples of luminance maps; (2) using the sparse samples to train a DNN that estimates the light transport model, and (3) predicting annual luminance maps using the DNN.
Photon mapping in image-based visual comfort assessments with BSDF models of high resolution
Published in Journal of Building Performance Simulation, 2019
The recursive simulation of light propagation in ray-tracing leads to a tree of rays. These are commonly classified by a formalized ray notation as listed in Table 1 (Heckbert 1990; Veach 1997). Hybrid BRT as implemented in RADIANCE replicates numerous mechanisms of light transport occurring in buildings, lending itself to applications in lighting design, daylighting and building design, in the form E(S*)([D|G]*)L for deterministic, and E(S*)[D|G]([D|G]+)L for stochastic ray-tracing. However, both algorithms are not capable to account for primary or secondary caustics ED([S|G]+)(D*)L (Arvo et al. 2001). Photon Mapping (PM) is a bidirectional algorithm that addresses this limitation and allows to simulate light transport in optically complex scenes (Jensen 2001). Its integration in RADIANCE allows to model light redirection by non-planar reflectors and refracting structures that is not properly accounted for by BRT (Schregle, Grobe, and Wittkopf 2015). Light redirecting elements can be geometrically modelled as any other parts of the scene and, unlike the utilization of pre-computed BSDFs, do not require any pre-processing. Recent enhancements of the RADIANCE PHOTON MAP, such as its Out-of-Core (OoC) data-structure to store large amounts of photons, and the introduction of the CONTRIBUTION PHOTON MAP allow to employ the module in illuminance-based Climate-Based Daylight Modelling (CBDM) techniques (Schregle 2015; Schregle et al. 2015; Bauer and Wittkopf 2016; Schregle, Grobe, and Wittkopf 2016).