Applying a-priori knowledge for compressing digital elevation models

  • Authors:

  • Giovanni Guzmán;Rolando Quintero;Miguel Torres;Marco Moreno

  • Affiliations:

  • Centre for Computer Research, National Polytechnical Institute, Mexico City, Mexico;Centre for Computer Research, National Polytechnical Institute, Mexico City, Mexico;Centre for Computer Research, National Polytechnical Institute, Mexico City, Mexico;Centre for Computer Research, National Polytechnical Institute, Mexico City, Mexico

  • Venue:
  • KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
  • Year:
  • 2006

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Abstract

Up-to-date, some algorithms related to compress digital elevation models (DEMs) or high-resolution DEMs, use wavelet and JPEG-LS encoding approaches to generate compressed DEM files with good compression factor. However, to access the original data (elevation values), it is necessary to decompress whole model. In this paper, we propose an algorithm oriented to compress a digital elevation model, which is based on a sequence of binary images encoded using RLE compression technique, according to a specific height (contour lines). The main goal of our algorithm is to obtain specific parameters of the DEM (altitudes and contours lines) without using a decompression stage, because the information is directly read from the compressed DEM.