@inproceedings {454,
	title = {Multiresolution statistical analysis and assimilation of large ocean data sets},
	booktitle = {20th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
	year = {1995},
	abstract = {<p>A significant problem in oceanographic remote sensing is the dense gridding or smoothing of sparsely sampled altimetric data. The smoothing of altimetric measurements has an application much broader than just the regular production of elevation maps for oceanographers, however. In particular, the ability to estimate ocean circulation patterns from altimetric data can serve as an important measure for the verification of ocean acoustic tomographic results. The authors present a multiscale technique capable of extremely efficient interpolation of altimetric data: about 256000 estimates and estimation error variances are computed in one minute on a Sun Sparc-10. They also demonstrate how similar techniques may be used to directly estimate the surface gradient and biases in the geoid-model error</p>
},
	keywords = {assimilation, biases, elevation maps, estimation error, geodesy, geoid-model error, geophysical signal processing, gridding, interpolation, large ocean data sets, multiresolution statistical analysis, multiscale technique, ocean acoustic tomographic results, ocean circulation patterns, oceanographic remote sensing, oceanographic techniques, parameter estimation, radar altimetry, radar signal processing, remote sensing by radar, signal resolution, smoothing, smoothing methods, sparsely sampled altimetric data, statistical analysis, surface gradient},
	doi = {http://dx.doi.org/10.1109/ICASSP.1995.479422},
	author = {P Fieguth and W C Karl and A S Willsky}
}
