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International Journal of Imaging Systems and Technology 21, 1 (2011) 28-36
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Tiled top-down combinatorial pyramids for large images representation
Romain Goffe ( ) 1, Luc Brun 2, Guillaume Damiand 3
FOGRIMMI Collaboration(s)
(02/2011)

The uprising number of applications that involve very large images with resolutions greater than 30\,000$\times$30\,000 raises major memory management issues. Firstly, the amount of data usually prevents such images from being processed globally and therefore, designing a global image partition raises several issues. Secondly, a multi-resolution approach is necessary since an analysis only based on the highest resolution may miss global features revealed at lower resolutions. This paper introduces the tiled top-down pyramidal framework which addresses these two main constraints. Our model provides a full representation of multi-resolution images with both geometrical and topological relationships. The advantage of a top-down construction scheme is twofold: the focus of attention only refines regions of interest which results in a reduction of the amount of required memory and in a refinement process that may take into account hierarchical features from previous segmentations. Moreover, the top-down model is combined with a decomposition in tiles to provide an accurate memory bounding while allowing global analysis of large images.
1 :  XLIM (XLIM)
CNRS : UMR6172 – Université de Limoges
2 :  Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen (GREYC)
CNRS : UMR6072 – Université de Caen Basse-Normandie – Ecole Nationale Supérieure d'Ingénieurs de Caen
3 :  Laboratoire d'InfoRmatique en Images et Systèmes d'Information (LIRIS)
CNRS : UMR5205 – Université Claude Bernard - Lyon I – Université Lumière - Lyon II – Institut National des Sciences Appliquées (INSA) - Lyon – Ecole Centrale de Lyon
SIC
Image
Informatique/Traitement des images
irregular pyramid – topological model – tiled data structure – combinatorial map
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