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A recursive approach to Multiscalar Data Interpolation of sparsely sampled sea surface measurements at different spatial resolutions

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dc.contributor Universitat de Vic. Escola Politècnica Superior
dc.contributor Universitat de Vic. Grup de Recerca en Tecnologies Digitals
dc.contributor.author Reig Bolaño, Ramon
dc.contributor.author García Ladona, Emili
dc.contributor.author Parisi Baradad, Vicenç
dc.contributor.author Martí i Puig, Pere
dc.date.accessioned 2012-12-12T12:30:15Z
dc.date.available 2012-12-12T12:30:15Z
dc.date.created 2008
dc.date.issued 2008
dc.identifier.citation Reig, R. [et al.]. A recursive approach to multiscalar data interpolation of sparsely sampled sea surface measurements at different spatial resolutions. A: OCEANS MTS/IEEE. "OCEANS'08 MTS/IEEE KOBE-TECHNO-OCEAN'08 Conference and Exhibition : Voyage toward the future". Kobe: 2008. ca_ES
dc.identifier.isbn 978-1-4244-2126-8
dc.identifier.uri http://hdl.handle.net/10854/1952
dc.description.abstract Abstract- In many oceanographic studies there is a need to reconstruct a signal from a set of sparse measurements. We propose an algorithm to iteratively approximate the intermediate values between irregularly sampled data, when a set of sparse values at coarser scales is known. This is possible when there is an approximation to a model for the multiresolution decomposition/reconstruction scheme of the dataset. Although the problem is ill-posed, this approach gives an easy scheme to interpolate the values of a signal using all the information available at different resolutions. This reconstruction method could be used as an extension of any interpolation method to optimize the multiresolution sparse data fusion. A simplified one-dimensional case illustrates the explanation; it is an algorithm based on a recursive scheme of a fast dyadic wavelet transform and its inversion, using a filter bank analysis/synthesis implementation for the wavelet transforms model. This can be a basis method suitable for applied cases where there are sparse measures from different instruments that are sensing the same scene simultaneously with several resolutions. Extensions of the method to sparse multiresolution dataset with higher dimensions (images or vector fields) also offer some promising preliminary results ca_ES
dc.format application/pdf
dc.format.extent 7 p. ca_ES
dc.language.iso eng ca_ES
dc.publisher IEEE ca_ES
dc.rights (c) IEEE
dc.rights Tots els drets reservats ca_ES
dc.subject.other Tractament del senyal ca_ES
dc.subject.other Imatges -- Processament
dc.title A recursive approach to Multiscalar Data Interpolation of sparsely sampled sea surface measurements at different spatial resolutions ca_ES
dc.type info:eu-repo/semantics/conferenceObject ca_ES
dc.identifier.doi https://doi.org/10.1109/OCEANSKOBE.2008.4530949
dc.relation.publisherversion http://ieeexplore.ieee.org/
dc.rights.accesRights info:eu-repo/semantics/closedAccess ca_ES

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