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Multiresolution image registration based on tree data structures

This paper presents a new approach for image registration based on the partitioning of the two source images in binary-space and quadtree structures, obtained with a maximum mutual information gain algorithm. Two different implementation approaches that differ in the level at which information is considered have been studied. The first works at pixel level using the simplified images directly, while the second works at node level dealing with the tree data structure. The obtained results show an outstanding accuracy and robustness of the proposed methods. In particular, the use of binary-space partitioned images drastically reduces the grid effects in comparison with regular downsampled images. An important advantage of our approach comes from the reduced size of the data structures corresponding to the simplified images, which makes this method appropriate to be applied in a multiresolution framework and telemedicine applications

Thanks to Dr. Narcis Coll for his help on this paper. Our work has been funded in part with Grant Numbers TIN2010-21089-C03-01 from the Spanish Government and 2009-SGR-643 from the Catalan Government

漏 Graphical Models, 2011. vol. 73, p. 111-126

Elsevier

Author: Bardera i Reig, Antoni
Boada, Imma
Feixas Feixas, Miquel
Rigau Vilalta, Jaume
Sbert, Mateu
Date: 2011 July 1
Abstract: This paper presents a new approach for image registration based on the partitioning of the two source images in binary-space and quadtree structures, obtained with a maximum mutual information gain algorithm. Two different implementation approaches that differ in the level at which information is considered have been studied. The first works at pixel level using the simplified images directly, while the second works at node level dealing with the tree data structure. The obtained results show an outstanding accuracy and robustness of the proposed methods. In particular, the use of binary-space partitioned images drastically reduces the grid effects in comparison with regular downsampled images. An important advantage of our approach comes from the reduced size of the data structures corresponding to the simplified images, which makes this method appropriate to be applied in a multiresolution framework and telemedicine applications
Thanks to Dr. Narcis Coll for his help on this paper. Our work has been funded in part with Grant Numbers TIN2010-21089-C03-01 from the Spanish Government and 2009-SGR-643 from the Catalan Government
Format: application/pdf
ISSN: 1524-0703
Document access: http://hdl.handle.net/10256/11679
Language: eng
Publisher: Elsevier
Collection: MICINN/PN 2011-2013/TIN2010-21089-C03-01
AGAUR/2009-2014/2009 SGR-643
Reproducci贸 digital del document publicat a: http://dx.doi.org/10.1016/j.gmod.2011.01.001
Articles publicats (D-IMA)
Is part of: 漏 Graphical Models, 2011. vol. 73, p. 111-126
Rights: Tots els drets reservats
Subject: Registre d鈥檌matges
Image registration
Imatges -- Processament -- T猫cniques digitals
Image processing -- Digital techniques
Title: Multiresolution image registration based on tree data structures
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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