Illumination demultiplexing from a single image

  • Authors:
  • Christine Chen;Daniel Vaquero;Matthew Turk

  • Affiliations:
  • ETH Zürich, Switzerland;UC Santa Barbara, CA, USA;UC Santa Barbara, CA, USA

  • Venue:
  • ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
  • Year:
  • 2011

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Abstract

A class of techniques in computer vision and graphics is based on capturing multiple images of a scene under different illumination conditions. These techniques explore variations in illumination from image to image to extract interesting information about the scene. However, their applicability to dynamic environments is limited due to the need for robust motion compensation algorithms. To overcome this issue, we propose a method to separate multiple illuminants from a single image. Given an image of a scene simultaneously illuminated by multiple light sources, our method generates individual images as if they had been illuminated by each of the light sources separately. To facilitate the illumination separation process, we encode each light source with a distinct sinusoidal pattern, strategically selected given the relative position of each light with respect to the camera, such that the observed sinusoids become independent of the scene geometry. The individual illuminants are then demultiplexed by analyzing local frequencies. We show applications of our approach in image-based relighting, photometric stereo, and multiflash imaging.