A Statistical Multiscale Approach to Mapping Altimetric Data

A challenging problem in oceanography is the dense estimation of the surface of the ocean in a statistically meaningful manner, given sparse and irregularly sampled measurements of the surface. A previously devel-oped highly efficient multiscale estimation framework is shown to be an appropriate tool for this task, and we demonstrate the manner of application and present experimental results. The algorithm is capable of computing 250,000 surface estimates of the ocean with error statistics in five seconds on a Sparc workstation