Discrete Dynamics in Nature and Society
Volume 2007 (2007), Article ID 62137, 12 pages
The Effect of Gaussian Blurring on the Extraction of Peaks and Pits from Digital Elevation Models
1Faculty of Engineering and Technology, Multimedia University, Jalan Air Keroh Lama, Melaka 75450, Malaysia
2Science and Technology Research Institute for Defence (STRIDE), Ministry of Defence, Bahagian Teknologi Maritim, D/A KD Malaya, Pangkalan TLDM, Perak 32100, Lumut, Malaysia
Received 27 December 2005; Revised 27 November 2006; Accepted 28 November 2006
Copyright © 2007 A. Pathmanabhan and S. Dinesh. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Gaussian blurring is an isotropic smoothing operator that is used to remove noise and detail from images. In this paper, the effect of Gaussian blurring on the extraction of peaks and pits from digital elevation models (DEMs) is studied. First, a mathematical
morphological-based algorithm to extract peaks and pits from DEMs is developed.
Gaussian blurring is then implemented on the global digital elevation model
(GTOPO30) of Great Basin using Gaussian kernels of different sizes and standard
deviation values. The number of peaks and pits extracted from the resultant DEMs is
computed using connected component labeling and the results are compared. The
application of Gaussian blurring to perform the treatment of spurious peaks and pits in
DEMs is also discussed. This work is aimed at studying the capabilities of Gaussian
blurring in the modeling of objects and processes operating within an environment.