Weak statistical constraints for variational stereo imaging of oceanic waves

Authors:
Guillermo Gallego;Anthony Yezzi;Francesco Fedele;Alvise Benetazzo
Affiliations:
School of Electrical Engineering, Georgia Institute of Technology, Atlanta;School of Electrical Engineering, Georgia Institute of Technology, Atlanta;School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta;CNR-ISMAR, Venice, Italy
Venue:
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Year:
2011

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Abstract

We develop an observational technique for the stereoscopic reconstruction of the wave form of oceanic sea states via a variational stereo method. In the context of active surfaces, the shape and radiance of the wave surface are obtained as minimizers of an energy functional that combines image observations and smoothness priors. To obey the quasi Gaussianity of oceanic waves observed in nature, a given statistical wave law is enforced in the stereo variational framework as a weak constraint. Multigrid methods are then used to solve the partial differential equations derived from the optimality conditions of the augmented energy functional. An application of the developed method to two sets of experimental stereo data is finally presented.