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Photon Parameterisation for Robust Relaxation Constraints
Author(s) -
Spencer B.,
Jones M.W.
Publication year - 2013
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12028
Subject(s) - computer science , relaxation (psychology) , photon , algorithm , computer graphics (images) , computer vision , artificial intelligence , theoretical computer science , mathematical optimization , mathematics , physics , optics , psychology , social psychology
Abstract This paper presents a novel approach to detecting and preserving fine illumination structure within photon maps. Data derived from each photon's primal trajectory is encoded and used to build a high‐dimensional kd‐tree. Incorporation of these new parameters allows for precise differentiation between intersecting ray envelopes, thus minimizing detail degradation when combined with photon relaxation. We demonstrate how parameter‐aware querying is beneficial in both detecting and removing noise. We also propose a more robust structure descriptor based on principal components analysis that better identifies anisotropic detail at the sub‐kernel level. We illustrate the effectiveness of our approach in several example scenes and show significant improvements when rendering complex caustics compared to previous methods.