Compression-based Image Registration
dc.contributor.author
dc.date.accessioned
2010-09-28T11:21:41Z
dc.date.available
2010-08-10T09:04:05Z
2010-09-28T11:21:41Z
dc.date.issued
2006-07
dc.identifier.citation
Bardera, Antoni, Feixas, Miquel, Boada, Imma, i Sbert, Mateu (2006). Compression-based Image Registration. IEEE International Symposium on Information Theory, 2006, 436 - 440. Recuperat 28 setembre 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4035998
dc.identifier.isbn
1-4244-0505-X
dc.identifier.uri
dc.description.abstract
Image registration is an important component of image analysis used to align two or more images. In this paper, we present a new framework for image registration based on compression. The basic idea underlying our approach is the conjecture that two images are correctly registered when we can maximally compress one image given the information in the other. The contribution of this paper is twofold. First, we show that the image registration process can be dealt with from the perspective of a compression problem. Second, we demonstrate that the similarity metric, introduced by Li et al., performs well in image registration. Two different versions of the similarity metric have been used: the Kolmogorov version, computed using standard real-world compressors, and the Shannon version, calculated from an estimation of the entropy rate of the images
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
IEEE
dc.relation.isformatof
Reproducció digital del document publicat a: http://dx.doi.org/10.1109/ISIT.2006.261706
dc.relation.ispartof
© IEEE International Symposium on Information Theory, 2006, p. 436-440
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Articles publicats (D-IMA)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Compression-based Image Registration
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.identifier.doi