A model-based expansion on interpolation for multiresolution sparse data
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2099/4928
Tipus de documentArticle
Data publicació2008-04-08
EditorSARTI (Technological Development Centre of Remote Acquisition and Data processing Systems)
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement-NoComercial-SenseObraDerivada 2.5 Espanya
Abstract
This paper addresses the interpolation of sparse irregular data when
these sparse data belong to diff erent scales. 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 if there is a characterized model for the
multiresolution decomposition / reconstruction scheme of the dataset.
Although the problem is ill-posed, and there are infi nite solutions,
this approach gives an easy scheme to interpolate the values
of a signal using all the information available at diff erent scales. This
reconstruction method could be used as an extension on any interpolation.
A simplifi ed one-dimensional case illustrates the explanation;
the scheme is based on a fast dyadic wavelet transform and its
inversion, using a fi lter 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 diff erent instruments
that are sensing the same scene simultaneously with several
resolutions. Extensions of the method to sparse multiresolution
data with higher dimensions (images or vector fi elds) also off er some
promising preliminary results.
CitacióReig Bolaño, R. [et al.]. A model-based expansion on interpolation for multiresolution sparse data. "Instrumentation viewpoint", 8 Abril 2008, vol. 2007, núm. 6, p. 82-83.
ISSN1886-4864
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