Título
Regularized quadratic cost function for oriented fringe-pattern filtering
Autor
José de Jesús Villa Hernández
JOSE ISMAEL DE LA ROSA VARGAS
Nivel de Acceso
Acceso Abierto
Materias
Resumen o descripción
We use the regularization theory in a Bayesian framework to derive a quadratic cost function for denoising
fringe patterns. As prior constraints for the regularization problem, we propose a Markov random field
model that includes information about the fringe orientation. In our cost function the regularization term
imposes constraints to the solution (i.e., the filtered image) to be smooth only along the fringe’s tangent direction.
In this way as the fringe information and noise are conveniently separated in the frequency space,
our technique avoids blurring the fringes. The attractiveness of the proposed filtering method is that the
minimization of the cost function can be easily implemented using iterative methods. To show the performance
of the proposed technique we present some results obtained by processing simulated and real fringe
patterns.
Producción Científica de la Universidad Autónoma de Zacatecas UAZ
Fecha de publicación
1 de junio de 2009
Tipo de publicación
Artículo
Recurso de información
Formato
application/pdf
Idioma
Español
Audiencia
Público en general
Repositorio Orígen
Repositorio Institucional Caxcán
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