Color-accurate underwater imaging using perceptual adaptive illumination

Iuliu Vasilescu, Carrick Detweiler, Daniela Rus

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Capturing color in water is challenging due to the heavy non-uniform attenuation of light in water across the visible spectrum, which results in dramatic hue shifts toward blue. Yet observing color in water is important for monitoring and surveillance as well as marine biology studies related to species identification, individual and group behavior, and ecosystem health and activity monitoring. Underwater robots are equipped with motor control for large scale transects but they lack sensors that enable capturing color-accurate underwater images. We present a method for color-accurate imaging in water called perceptual adaptive illumination. This method dynamically mixes the illumination of an object in a distance-dependent way using a controllable, multi-color light source. The color mix compensates correctly for color loss and results in an image whose color composition is equivalent to rendering the object in air. Experiments were conducted with a color palette in the pool and at three different coral reefs sites, and with an underwater robot collecting image data with the new sensor.

Original languageEnglish (US)
Pages (from-to)285-296
Number of pages12
JournalAutonomous Robots
Volume31
Issue number2-3
DOIs
StatePublished - Oct 2011

Keywords

  • Accurate colors
  • Adaptive illumination
  • Color rendering index
  • Underwater imaging

ASJC Scopus subject areas

  • Artificial Intelligence

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