Hierarchical Segmentation of Sparse Surface Data Using Energy-Minimization Approach

  • Raid Al-Tahir


The main objective for this research is to develop an algorithm that produces a dense representation of a surface from a sparse set of observations and facilitates preliminary labeling of discontinuities in the surface. The solution to these issues is of a great interest to the new trends and applications in digital photogrammetry, particularly for large-scale urban imagery.

This study adopts the approach of a concurrent interpolation of the surface and detection of its discontinuities by the weak membrane. The solution was achieved through developing a multigrid implementation of the Graduate Non-Convexity (GNC) algorithm. The conducted experiments proved that the developed method is adequate and applicable for dealing with large-scale images of urban areas as it was successful in producing a realistic surface representation and fulfilling other set criteria.

Key words

Surface Reconstruction Discontinuioty Detection Multigrid Regularization 


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Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • Raid Al-Tahir
    • 1
  1. 1.Centre for Caribbean Land and Environmental Appraisal Research (CLEAR) Department of Surveying and Land InformationThe University of the West IndiesTrinidad and Tobago

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