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Scratch iridescence: wave-optical rendering of diffractive surface structure

Published: 20 November 2017 Publication History

Abstract

The surface of metal, glass and plastic objects is often characterized by microscopic scratches caused by manufacturing and/or wear. A closer look onto such scratches reveals iridescent colors with a complex dependency on viewing and lighting conditions. The physics behind this phenomenon is well understood; it is caused by diffraction of the incident light by surface features on the order of the optical wavelength. Existing analytic models are able to reproduce spatially unresolved microstructure such as the iridescent appearance of compact disks and similar materials. Spatially resolved scratches, on the other hand, have proven elusive due to the highly complex wave-optical light transport simulations needed to account for their appearance. In this paper, we propose a wave-optical shading model based on non-paraxial scalar diffraction theory to render this class of effects. Our model expresses surface roughness as a collection of line segments. To shade a point on the surface, the individual diffraction patterns for contributing scratch segments are computed analytically and superimposed coherently. This provides natural transitions from localized glint-like iridescence to smooth BRDFs representing the superposition of many reflections at large viewing distances. We demonstrate that our model is capable of recreating the overall appearance as well as characteristic detail effects observed on real-world examples.

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  1. Scratch iridescence: wave-optical rendering of diffractive surface structure

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      cover image ACM Transactions on Graphics
      ACM Transactions on Graphics  Volume 36, Issue 6
      December 2017
      973 pages
      ISSN:0730-0301
      EISSN:1557-7368
      DOI:10.1145/3130800
      Issue’s Table of Contents
      © 2017 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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      Publication History

      Published: 20 November 2017
      Published in TOG Volume 36, Issue 6

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      Author Tags

      1. SVBRDF
      2. diffraction
      3. iridescence

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      • (2024)Physically-based data augmentation for deep learning-enabled automated visual inspection of scratches2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)10.1109/CASE59546.2024.10711456(1644-1649)Online publication date: 28-Aug-2024
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