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Morse description and geometric encoding of digital elevation maps.

Andrés Solé1, Vicent Caselles, Guillermo Sapiro

  • 1Department de Tecnologia, Universitat Pompeu-Fabra, 08003 Barcelona, Spain.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|September 29, 2004
PubMed
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This study introduces novel geometric structures for image topography, enabling efficient encoding of digital elevation maps (DEMs). The developed compression scheme achieves high data reduction while controlling errors for DEM applications.

Area of Science:

  • Geographic Information Science
  • Computer Vision
  • Digital Image Processing

Background:

  • Digital Elevation Models (DEMs) are crucial for geographic analysis.
  • Efficient compression of DEMs is vital for storage and transmission.
  • Existing methods may lack error control or optimal compression ratios.

Purpose of the Study:

  • To develop novel geometric structures for topographic image representation.
  • To create an efficient compression scheme for DEMs based on these structures.
  • To ensure controlled error in the decoded elevation data.

Main Methods:

  • Computation of Morse-topological structure of images.
  • Computation of simplified drainage structure of images.
  • Integration of geometric representation with interpolation and lossless compression algorithms.

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Main Results:

  • Demonstration of Morse and drainage structures as effective bases for encoding.
  • Development of a DEM compression algorithm achieving high compression ratios.
  • Validation of controlled maximum error in decoded elevation maps.

Conclusions:

  • The proposed geometric approach provides an efficient basis for DEM compression.
  • The developed algorithm offers a practical solution for handling large DEM datasets.
  • The method is suitable for applications requiring precise elevation data integrity.