@article{GBD11,
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 = {http://dx.doi.org/10.1002/ima.20270},
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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