A Fast Algorithm to Estimate the Deepest Points of Lakes for Regional Lake Registration

When conducting image registration in the U.S. state of Alaska, it is very difficult to locate satisfactory ground control points because ice, snow, and lakes cover much of the ground. However, GCPs can be located by seeking stable points from the extracted lake data. This paper defines a process to...

Full description

Saved in:
Bibliographic Details
Published in:PloS one 2015-12, Vol.10 (12), p.e0144700-e0144700
Main Authors: Shen, Zhanfeng, Yu, Xinju, Sheng, Yongwei, Li, Junli, Luo, Jiancheng
Format: Article
Language:English
Subjects:
Algorithms
Complexity
Computation
Efficiency
Equalization
Geometry
Ground based control
Ice cover
Image registration
Lakes
Methods
Morphology
Parallel processing
Partial differential equations
Polygons
Registration
Remote sensing
United States
Voronoi graphs
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:When conducting image registration in the U.S. state of Alaska, it is very difficult to locate satisfactory ground control points because ice, snow, and lakes cover much of the ground. However, GCPs can be located by seeking stable points from the extracted lake data. This paper defines a process to estimate the deepest points of lakes as the most stable ground control points for registration. We estimate the deepest point of a lake by computing the center point of the largest inner circle (LIC) of the polygon representing the lake. An LIC-seeking method based on Voronoi diagrams is proposed, and an algorithm based on medial axis simplification (MAS) is introduced. The proposed design also incorporates parallel data computing. A key issue of selecting a policy for partitioning vector data is carefully studied, the selected policy that equalize the algorithm complexity is proved the most optimized policy for vector parallel processing. Using several experimental applications, we conclude that the presented approach accurately estimates the deepest points in Alaskan lakes; furthermore, we gain perfect efficiency using MAS and a policy of algorithm complexity equalization.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0144700