Date
2003
Dewey
Probabilités et mathématiques appliquées
Sujet
Projective registration; Similarity estimation by level sets; Image registration
Book title
Geometric Level Set Methods in Imaging, Vision, and Graphics
Author
Paragios, Nikos; Osher, Stanley
Publisher
Springer
Publisher city
Berlin
Year
2003
Pages number
513
ISBN
978-0-387-95488-2
Author
Dibos, Françoise
Koepfler, Georges
Monasse, Pascal
Type
Chapitre d'ouvrage
Item number of pages
271-295
Abstract (EN)
Besides stating the problem of image registration this chapter is built on the following parts : 1) Similarity estimation by level sets. We use the Fast Level Sets Transform (see the chapter on TV minimization) to extract reliable features from both images. To each feature we associate similarity invariants, then we consider pairs of features (F1, F2), where F1 is in image 1 and F2 in image 2, that can match modulo a similarity. We call these pairs correspondences. These correspondences vote for the four parameters of the global similarity. The set of four parameters that gets the maximum number of votes is the estimated similarity. 2) Projective registration. Thanks to a new model for projective deformation, the registration group, we are able, after elimination of the pure projective deformation (i.e. 2 parameters), to reduce the projective matching to a similarity matching.