author = {Romain {Goffe} and Luc {Brun} and Guillaume {Damiand}},
  title = {Tiled top–down combinatorial pyramids for large images representation},
  journal = {International Journal of Imaging Systems and Technology},
  volume = {21},
  number = {1},
  publisher = {Wiley Subscription Services, Inc., A Wiley Company},
  issn = {1098-1098},
  url = {},
  doi = {10.1002/ima.20270},
  pages = {28--36},
  keywords = {Irregular pyramid; Topological model; Tiled data structure; Combinatorial map;},
  year = {2011},
  pdf = {GoffeAl11-IJIST.pdf},
  abstract = {
 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.

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