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Tiled top–down combinatorial pyramids for large images representation
Author(s) -
Goffe Romain,
Brun Luc,
Damiand Guillaume
Publication year - 2011
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.20270
Subject(s) - computer science , bounding overwatch , focus (optics) , representation (politics) , partition (number theory) , process (computing) , decomposition , image (mathematics) , scheme (mathematics) , artificial intelligence , algorithm , mathematics , ecology , mathematical analysis , physics , combinatorics , politics , law , political science , optics , biology , operating system
The uprising number of applications that involve very large images with resolutions greater than 30,000 × 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 multiresolution approach is necessary since an analysis only based on the highest resolution may miss global features revealed at lower resolutions. This article introduces the tiled top–down pyramidal framework which addresses these two main constraints. Our model provides a full representation of multiresolution 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 decomposition in tiles to provide an accurate memory bounding while allowing global analysis of large images. © 2011Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 28–36, 2011.