@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 = {

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

}, 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} } @inproceedings {459, title = {Multiresolution stochastic imaging of satellite oceanographic altimetric data}, booktitle = {Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference}, year = {1994}, abstract = {

Large data assimilation problems present a number of challenges, many of which the authors\&$\#$39; multiscale estimation framework is capable of addressing. They demonstrate the application of their estimation framework to an oceanographic data assimilation problem of considerable interest: the smoothing of Topex/Poseidon ocean altimetric data. they produce surface estimates and error statistics on a 512 times;512 grid in one minute on a Sparc-10. Using a generic surface reconstruction problem they demonstrate alternative uses of the multiscale framework: higher order state models, combining estimates from an ensemble of trees, and overlapping tree models

}, keywords = {error statistics, geophysical signal processing, higher order state models, image reconstruction, large data assimilation problems, multiresolution stochastic imaging, multiscale estimation framework, multiscale framework, oceanographic techniques, overlapping tree models, radar altimetry, radar imaging, remote sensing by radar, satellite oceanographic altimetric data, smoothing methods, state estimation, stochastic processes, surface estimates, surface reconstruction problem, Topex/Poseidon ocean altimetric data, trees, trees (mathematics)}, doi = {http://dx.doi.org/10.1109/ICIP.1994.413519}, author = {P Fieguth and A S. Willsky and W C. Karl} } @inproceedings {460, title = {Multiresolution stochastic imaging of satellite oceanographic altimetric data}, booktitle = {Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference}, year = {1994}, abstract = {

Large data assimilation problems present a number of challenges, many of which the authors\&$\#$39; multiscale estimation framework is capable of addressing. They demonstrate the application of their estimation framework to an oceanographic data assimilation problem of considerable interest: the smoothing of Topex/Poseidon ocean altimetric data. they produce surface estimates and error statistics on a 512 times;512 grid in one minute on a Sparc-10. Using a generic surface reconstruction problem they demonstrate alternative uses of the multiscale framework: higher order state models, combining estimates from an ensemble of trees, and overlapping tree models

}, keywords = {error statistics, geophysical signal processing, higher order state models, image reconstruction, large data assimilation problems, multiresolution stochastic imaging, multiscale estimation framework, multiscale framework, oceanographic techniques, overlapping tree models, radar altimetry, radar imaging, remote sensing by radar, satellite oceanographic altimetric data, smoothing methods, state estimation, stochastic processes, surface estimates, surface reconstruction problem, Topex/Poseidon ocean altimetric data, trees, trees (mathematics)}, doi = {http://dx.doi.org/10.1109/ICIP.1994.413519}, author = {P Fieguth and A S. Willsky and W C. Karl} } @inproceedings {461, title = {Multiresolution stochastic processing of Topex/Poseidon oceanographic altimetry}, booktitle = {IEEE OCEANS{\textquoteright}94}, year = {1994}, abstract = {

Remarkable advances in remote sensing are producing measurements on increasingly finer grids, offering the possibility of a far better understanding and characterization of the ocean surface. The sheer quantity of measurements has rendered traditional data smoothing/assimilation algorithms obsolete however, even on high performance workstations; the basis of this paper is the application of an extremely fast multiresolution smoothing framework to ocean altimetry data. Using the previously developed multiresolution framework, a simple multiscale model is developed which captures the characteristic power-law spectrum of the ocean surface. Smoothing altimetric data and computing error variances on a grid of 512 by 512 points is accomplished in about 10 seconds on a SUN Sparc-10. Finally, further applications of this framework within the oceanographic context are discussed, including model identification and anomaly detection

}, keywords = {algorithm, data assimilation, data smoothing, geophysical signal processing, geophysics computing, measurement technique, multiresolution stochastic processing, multiscale model, ocean dynamics, ocean surface, oceanographic techniques, Poseidon, radar altimetry, radar applications, radar imaging, radar signal processing, Remote Sensing, remote sensing by radar, satellite remote sensing, sea surface, signal processsing, Topex}, doi = {http://dx.doi.org/10.1109/OCEANS.1994.363913}, author = {P Fieguth and W C. Karl and A S. Willsky} }