Regularization of inverse visual problems involving discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Surface Interpolation Using Hierarchical Basis Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Simple and Efficient Connected Components Labeling Algorithm
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
An Interpretation System for Cadastral Maps
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Agent-based parallel recognition method of contour lines
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
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Thin plate spline interpolation is a widely used approach to generate a digital elevation model (DEM) from contour lines and scattered data. In practice, contour maps are scanned and vectorized, and after resampling in the target grid resolution, interpolation is performed. In this paper we demonstrate the limited accuracy of this process, and propose a high-resolution processing method (without vectorization) that ensures maximum utilization of information in the source data. First, we discuss the mathematical background of thin plate spline interpolation, and explain the multigrid relaxation principle used to speed up convergence. After, we will show why fine tuning is necessary, especially when contour lines and elevation points are processed at the same time. Finally, our own contour thinning method that produces a significant reduction of elevation bias is described.