A new microflake model with microscopic self-shadowing for accurate volume downsampling

Guillaume Loubet 1 Fabrice Neyret 1
1 MAVERICK - Models and Algorithms for Visualization and Rendering
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : Naïve linear methods for downsampling high-resolution microflake volumes often produce inaccurate appearance, especially when input voxels are very opaque. Preserving correct appearance at all resolutions requires taking into account masking-shadowing effects that occur between and inside dense input voxels. We introduce a new microflake model whose additional parameters characterize self-shadowing effects at a microscopic scale. We provide an anisotropic self-shadowing function and microflake distributions for which the scattering coefficients and the phase functions of our model have closed-form expressions. We use this model in a new downsampling approach in which scattering parameters are computed from local estimations of self-shadowing probabilities in the input volume. Unlike previous work, our method handles datasets with spatially varying scattering parameters, semi-transparent volumes and datasets with intricate silhouettes. We show that our method generates LoDs with correct transparency and consistent appearance through scales for a wide range of challenging datasets, allowing for huge memory savings and efficient distant rendering without loss of quality.
Type de document :
Article dans une revue
Computer Graphics Forum, Wiley, 2018, 37 (2), pp.111-121. 〈10.1111/cgf.13346〉
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Soumis le : mardi 6 février 2018 - 14:03:02
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Guillaume Loubet, Fabrice Neyret. A new microflake model with microscopic self-shadowing for accurate volume downsampling. Computer Graphics Forum, Wiley, 2018, 37 (2), pp.111-121. 〈10.1111/cgf.13346〉. 〈hal-01702000〉



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