Probabilistic classification of seafloor using RGB imagery

Color is typically an important cue for classification purposes. However, use of trichromatic cameras underwater often leads to deceiving results due to 1) wavelength-dependent absorption of light by water and dissolved organic matter, and 2) broadband response of camera sensors. We are developing methods to
process underwater imagery in a probabilistic manner, utilizing known properties of a camera and spectra of main seafloor sediments.
Faculty: Prof. Yuri Rzhanov, Prof Jennifer Dijkstra

For more information contact Prof. Yuri Rzhanov