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Multipole-motivated reduced-state estimation

This paper discusses efficient solutions to large-scale two-dimensional estimation problems, using reduced state methods motivated by the multipole method of mathematical physics. The work is mainly exploratory, building on past efforts in multiscale statistical signal modeling and estimation. We will illustrate applications to the estimation of Markov random field textures, with the motivation and goal the estimation of remotely-sensed fields.