Shading from shape, the eikonal equation solved by grey-weighted distance transform
Pattern Recognition Letters
Generalized geodesy via geodesic time
Pattern Recognition Letters
New Prospects in Line Detection by Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Unbiased Detector of Curvilinear Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Thin nets extraction using a multi-scale approach
Computer Vision and Image Understanding
A Minimum Cost Approach for Segmenting Networks of Lines
International Journal of Computer Vision
Semi-Automated Extraction of Rivers from Digital Imagery
Geoinformatica
Advances in the Analysis of Topographic Features on Discrete Images
DGCI '02 Proceedings of the 10th International Conference on Discrete Geometry for Computer Imagery
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
State of the art on automatic road extraction for GIS update: a novel classification
Pattern Recognition Letters
Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation
IEEE Transactions on Image Processing
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In this paper, we propose a new methodology for extracting river networks from satellite images. It combines morphological generalised geodesic transformations with hydrological overland flow simulations. The method requires the prior generation of a geodesic mask and a marker image by applying a series of transformations to the original image. These images are then combined so as to produce a pseudo digital elevation model whose valleys match the desired networks. The performance of the methodology is demonstrated for the extraction of river networks from a single band of a Landsat image. The method is generic in the sense that it can be extended for the extraction of other types of arborescent networks such as blood vessels in medical images.