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A Causal Extraction Scheme in Top-Down Pyramids for Large Images Segmentation

  • Romain Goffe
  • Guillaume Damiand
  • Luc Brun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6218)

Abstract

Applicative fields based on the analysis of large images must deal with two important problems. First, the size in memory of such images usually forbids a global image analysis hereby inducing numerous problems for the design of a global image partition. Second, due to the high resolution of such images, global features only appear at low resolutions and a single resolution analysis may loose important information. The tiled top-down pyramidal model has been designed to solve this two major challenges. This model provides a hierarchical encoding of the image at single or multiple resolutions using a top-down construction scheme. Moreover, the use of tiles bounds the amount of memory required by the model while allowing global image analysis. The main limitation of this model is the splitting step used to build one additional partition from the above level. Indeed, this step requires to temporary refine the split region up to the pixel levelwhich entails high memory requirements and processing time. In this paper, we propose a new splitting step within the tiled top-down pyramidal framework which overcomes the previously mentioned limitations.

Keywords

Irregular pyramid Topological model Tiled data structure Combinatorial map 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Romain Goffe
    • 1
  • Guillaume Damiand
    • 2
  • Luc Brun
    • 3
  1. 1.SIC-XLIM, Université de Poitiers, CNRS, UMR6172Futuroscope ChasseneuilFrance
  2. 2.LIRIS, Université de Lyon, CNRS, UMR5205VilleurbanneFrance
  3. 3.GREYC, ENSICAEN, CNRS, UMR6072CaenFrance

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