Título: Weighted Zernike polynomial fitting in steep corneas sampled in Cartesian grid
Autores: Espinosa Tomás, Julián
Pérez Rodríguez, Jorge
Mas Candela, David
Illueca Contri, Carlos
Fecha: 2011-02-21
2011-02-21
2010-09
2011-02
Publicador: RUA Docencia
Fuente:
Tipo: info:eu-repo/semantics/article
Tema: Corneal surface reconstruction
Zernike polynomials
Weighted least-squares fitting
Óptica
Descripción: Surfaces with radial structure do not fit well to squared detectors or sampling matrices. Cartesian grid sampling provides a different density of nodes in sectors. Zernike polynomials are a complete set of orthogonal polynomials defined on a unit disk often used as an expansion of such surfaces. In the fitting process, the sampling distribution is not usually taken into account and might have undesirable effects on the final parameter estimates. We propose applying weighted least-squares regression that compensates the unequal influence of sectors due to the sampling distribution, assigning a weight function to the nodes grid and thus providing a better fit in the central optical zone.
This work has been supported by the Generalitat Valenciana project no. GV/2009/002. J. Espinosa acknowledges the support of the Generalitat Valenciana through the project BEST/2010/209.
Idioma: Inglés

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