Physics – Atmospheric and Oceanic Physics
Scientific paper
2006-04-19
Physics
Atmospheric and Oceanic Physics
Scientific paper
An algorithm to estimate motion from satellite imagery is presented. Dense displacement fields are computed from time-separated images of of significant convective activity using a Bayesian formulation of the motion estimation problem. Ordinarily this motion estimation problem is ill-posed; there are far too many degrees of freedom than necessary to represent the motion. Therefore, some form of regularization becomes necessary and by imposing smoothness and non-divergence as desirable properties of the estimated displacement vector field, excellent solutions are obtained. Our approach provides a marked improvement over other methods in conventional use. In contrast to correlation based approaches, the displacement fields produced by our method are dense, spatial consistency of the displacement vector field is implicit, and higher-order and small-scale deformations can be easily handled. In contrast with optic-flow algorithms, we can produce solutions at large separations of mesoscale features between large time-steps or where the deformation is rapidly evolving.
Chatdarong Virat
Ravela Sai
No associations
LandOfFree
Rainfall Advection using Velocimetry by Multiresolution Viscous Alignment does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Rainfall Advection using Velocimetry by Multiresolution Viscous Alignment, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Rainfall Advection using Velocimetry by Multiresolution Viscous Alignment will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-237381