Feature preserving variational smoothing of terrain data

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Publication Type Journal Article
School or College College of Engineering
Department Electrical & Computer Engineering
Creator Tasdizen, Tolga; Whitaker, Ross T.
Title Feature preserving variational smoothing of terrain data
Date 2003
Description In this paper, we present a novel two-step, variational and feature preserving smoothing method for terrain data. The first step computes the field of 3D normal vectors from the height map and smoothes them by minimizing a robust penalty function of curvature. This penalty function favors piecewise planar surfaces; therefore, it is better suited for processing terrain data then previous methods which operate on intensity images. We formulate the total curvature of a height map as a function of its normals. Then, the gradient descent minimization is implemented with a second-order partial differential equation (PDE) on the field of normals. For the second step, we define another penalty function that measures the mismatch between the the 3D normals of a height map model and the field of smoothed normals from the first step. Then, starting with the original height map as the initialization, we fit a non-parametric terrain model to the smoothed normals minimizing this penalty function. This gradient descent minimization is also implemented with a second-order PDE. We demonstrate the effectiveness of our approach with a ridge/gully detection application.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Language eng
Bibliographic Citation Tasdizen, T., & Whitaker, R. (2003). Feature preserving variational smoothing of terrain data. 2nd International IEEE Workshop on Variational, Geometric and Level Set Methods in Computer Vision, October.
Rights Management (c) 2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Format Medium application/pdf
Format Extent 2,739,759 bytes
Identifier ir-main,15232
ARK ark:/87278/s61269rc
Setname ir_uspace
Date Created 2012-06-13
Date Modified 2021-05-06
ID 702603
Reference URL https://collections.lib.utah.edu/ark:/87278/s61269rc
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