Three-Dimensional Semiautomatic Road Extraction From a High-Resolution Aerial Image by Dynamic-Programming Optimization in the Object Space

• Published in: IEEE geoscience and remote sensing letters Vol. 7; no. 4; pp. 796 - 800
• Main Authors: Dal Poz, A P, Gallis, R A B, da Silva, J F C
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2010; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Curve fitting; Data mining; Digital; Digital elevation models; Dynamic programming; Dynamic programming (DP); Extraction; Feature extraction; image analysis; Image color analysis; Mathematical model; Mathematical models; Optimization; Optimization methods; remote sensing; Representations; Roads; Solid modeling
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2010.2047838

This letter proposes a method for 3-D semiautomatic road extraction from a single image by dynamic programming (DP), which requires a form of relief representation such as digital terrain model. Unlike traditional DP methodologies, this method relies on the DP algorithm to carry out the optimization process in the object space rather than in the image space. Road features are traced in the object space, implying the need for a rigorous mathematical model between image- and object-space points. The operator must measure a few seed points in the image space to coarsely describe the roads, which are then transformed into object space to initialize the DP optimization process. The results showed that the method usually works properly, even in the presence of anomalies along roads.