Institutional Repository [SANDBOX]
Technical University of Crete
EN  |  EL

Search

Browse

My Space

Non-parametric Identification of anisotropic (Elliptic) correlations in spatially distributed data sets

Chorti Arsenia, Christopoulos Dionysios

Simple record


URIhttp://purl.tuc.gr/dl/dias/E18AEC51-5D0C-44A2-9A6C-070C60CFA295-
Identifierhttps://ieeexplore.ieee.org/document/4626087-
Identifierhttps://doi.org/10.1109/TSP.2008.924144-
Languageen-
Extent14 pagesen
TitleNon-parametric Identification of anisotropic (Elliptic) correlations in spatially distributed data setsen
CreatorChorti Arseniael
CreatorChristopoulos Dionysiosen
CreatorΧριστοπουλος Διονυσιοςel
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryRandom fields are useful models of spatially variable quantities, such as those occurring in en- vironmental processes and medical imaging. The fluctuations obtained in most natural data sets are typically anisotropic. The parameters of anisotropy are often determined from the data by means of empirical methods or the computationally expensive method of maximum likelihood. In this paper we propose a systematic method for the identification of geometric (elliptic) anisotropy parameters of scalar fields. The proposed method is computationally efficient, non-parametric, non-iterative, and it applies to differentiable random fields with normal or lognormal probability density functions. Our approach uses sample based estimates of the random field spatial derivatives that we relate through closed form expressions to the anisotropy parameters. This paper focuses on two spatial dimensions. We investigate the performance of the method on synthetic samples with Gaussian and Mate ́rn correlations, both on regular and irregular lattices. The systematic anisotropy detection provides an important pre-processing stage of the data. Knowledge of the anisotropy parameters, followed by suitable rotation and rescaling transformations restores isotropy thus allowing classical interpolation and signal processing methods to be applied.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-09-25-
Date of Publication2008-
SubjectAnisotropic magnetoresistanceen
SubjectBiomedical imagingen
SubjectFluctuationsen
SubjectMaximum likelihood detectionen
SubjectMaximum likelihood estimationen
SubjectProbability density functionen
SubjectLatticesen
SubjectSignal restorationen
SubjectInterpolationen
SubjectSignal processingen
Bibliographic CitationA. Chorti and D.T. Hristopulos, "Non-parametric identification of anisotropic (Elliptic) correlations in spatially distributed data sets," IEEE Trans. Signal Process., vol. 56, no. 10, pp 4738-4751, Oct. 2008. doi: 10.1109/TSP.2008.924144en

Services

Statistics