A new wavelets image fusion strategy
| dc.contributor.author | Santos Peñas, Matilde | |
| dc.contributor.author | Pajares Martínsanz, Gonzalo | |
| dc.contributor.author | Portela, M. | |
| dc.contributor.author | Cruz García, Jesús Manuel de la | |
| dc.date.accessioned | 2023-06-20T19:01:05Z | |
| dc.date.available | 2023-06-20T19:01:05Z | |
| dc.date.issued | 2003 | |
| dc.description | © Springer-Verlag Berlin Heidelberg 2003. Iberian Conference on Pattern Recognition and Image Analysis (1st.Jun 04-06, 2003. Mallorca, España) | |
| dc.description.abstract | The aim of image fusion is to combine information from multiple images of the same scene. The result of image fusion is a new image,,which is more suitable for human and machine perception or further image-processing tasks such as segmentation, feature extraction and object recognition. Different fusion methods have been proposed in the literature. This paper presents new methods based on the computation of local and global gradient. A comparative analysis is carried out against other existing strategies. The results are encouraging. | |
| dc.description.department | Sección Deptal. de Arquitectura de Computadores y Automática (Físicas) | |
| dc.description.faculty | Fac. de Ciencias Físicas | |
| dc.description.refereed | TRUE | |
| dc.description.status | pub | |
| dc.eprint.id | https://eprints.ucm.es/id/eprint/26286 | |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.officialurl | http://link.springer.com/chapter/10.1007%2F978-3-540-44871-6_106# | |
| dc.identifier.relatedurl | http://link.springer.com/ | |
| dc.identifier.relatedurl | http://link.springer.com/content/pdf/10.1007%2F978-3-540-44871-6_106.pdf | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14352/59113 | |
| dc.journal.title | Pattern Recognition and Image Analysis, Proceedings | |
| dc.language.iso | eng | |
| dc.page.final | 926 | |
| dc.page.initial | 919 | |
| dc.publisher | Springer-Verlag Berlin | |
| dc.rights.accessRights | open access | |
| dc.subject.cdu | 004 | |
| dc.subject.keyword | Computer Science Artificial Intelligence | |
| dc.subject.keyword | Computer Science Theory and Methods | |
| dc.subject.keyword | Imaging Science and Photographic Technology | |
| dc.subject.ucm | Informática (Informática) | |
| dc.subject.unesco | 1203.17 Informática | |
| dc.title | A new wavelets image fusion strategy | |
| dc.type | journal article | |
| dc.volume.number | 2652 | |
| dcterms.references | [1] Z. Zhang and R.S. Blum, A categorization of Multiscale-Decomposition-Based Image Fusion Schemes with a Performance Study for a Digital Camera Application, Proceedings of the IEEE 87(8) (1999) 1315-1326. [2] H. Li, B.S. Manjunath, S.K. Mitra, Multisensor Image Fusion Using the Wavelet Transform, Graphical Models and Image Processing 57(3) (1995) 235-245. [3] P.J. Burt, E. Adelson, The Laplacian pyramid as a compact image code, IEEE Trans. Commun. 31 (1983) 532-540. [4] E. H. Adelson, C.H. Anderson, J.R. Bergen, P.J. Burt, J. Ogden, Pyramid methods in image processing, RCA Engineer, 29(6) (1984) 33-41. [5] T. Lindeberg, Scale-Space Theory in Computer Vision, Kluwer, Norwell: MA, 1994. [6] S. Mallat, A Wavelet Tour of Signal Processing, Academic Press, 2nd ed, 1999. [7] E.J. Stollnitz, T.D. DeRose, D.H. Salesin, Wavelets for Computer Graphics: A Primer, Part 1, IEEE Computer Graphics and Applications 15(3) (1995) 76-84. [8] I. Daubechies, Ten Lectures on Wavelets, SIAM, Philadelphia, 1992. [9] I. Daubechies, Orthonormal Bases of Compactly Supported Wavelets, Comm. Pure Applied Mathematics 41 (1988) 909-996. [10] J.L. Starck, F. Murtagh, A. Bijaoui, Image Processing and Data Analysis: The multiscale approach. Cambridge, University Press, 2000. [11] G. Pajares, J. M. de la Cruz, Visión por Computador: Imágenes Digitales y Aplicaciones, RA-MA: Madrid, 2001. | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 99cac82a-8d31-45a5-bb8d-8248a4d6fe7f | |
| relation.isAuthorOfPublication | 878e090e-a59f-4f17-b5a2-7746bed14484 | |
| relation.isAuthorOfPublication.latestForDiscovery | 99cac82a-8d31-45a5-bb8d-8248a4d6fe7f |
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