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Spatial and temporal surface interpolation using wavelet bases

Efficient solutions to spatial interpolation problems (e.g., regularization) and spatio-temporal interpolation problems (e.g., regularization plus Kalman filtering) can be obtained by using wavelet bases either for problem discretization or for preconditioning. Good approximate solutions can be obtained in only O(n) operations and O(n) storage locations, so that rear-real- time implementations are possible on standard microprocessors.