%0 Journal Article 
%A Morales Sánchez, Juan
%A Larrey Ruiz, Jorge
%A Sancho Gómez, José Luis
%T Regularización de situaciones de ambigüedad en el registro de imágenes mediante modelos duales
%D 2005
%U http://hdl.handle.net/10317/1341
%X Usually, the most critical step involved in image
registration is the image matching. A common methodology when
estimating the mapping that geometrically relates two images
typically consists of two separate and sequential stages: initial
feature matching estimation, and regularization for propagating
this matching over all image areas. Parametric models representing
fuzzy matching regions are proposed in order to support the
initial matching. The classical approach has a main drawback,
namely the detection of the common features is ambiguous when
there is more than one likely matching. To alleviate this problem,
the use of dual models to represent the high similarity regions is
also proposed in this paper. An averaged POCS (projection onto
convex sets) procedure, combined with regularization based on
deformable kernels, is used to solve the multiple-choice dilemma.
Implementation of these parametrization and regularization steps
is described throughout the paper. The proposed approach is
tested on a stereo-pair that presents multiple choices of similar
likelihood, with successful results.
%K Teoría de la Señal y las Comunicaciones
%K Modelo dual
%K Imágenes
%K Registro de imágenes
%K Pixel
%K Modelo paramétrico dual
%K Algoritmos de block matching
%K Dual model
%K Image
%K Image registration
%K Dual parametric model
%K Block matching algorithm
%~ GOEDOC, SUB GOETTINGEN