Semiautomatic road extraction by dynamic programming

Armin Gruen; Haihong Li

doi:10.1117/12.182868

17 August 1994 Semiautomatic road extraction by dynamic programming

Armin Gruen, Haihong Li

Proceedings Volume 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision; (1994) https://doi.org/10.1117/12.182868
Event: Spatial Information from Digital Photogrammetry and Computer Vision: ISPRS Commission III Symposium, 1994, Munich, Germany

Abstract

We propose a semi-automatic road extraction scheme which combines the wavelet decomposition for road sharpening and a model driven liner feature extraction algorithm based on dynamic programming. We have built a special wavelet for road sharpening, which has been implemented as a fast pyramidal algorithm. In the model driven feature extraction scheme, a road is represented by a generic road model with six photometric and geometric properties. This model is formulated by some constraints and a merit function which embodies a notion of the `best road segment,' and evaluated by a `time-delayed' dynamic programming algorithm. The mathematical foundation and issues relating to its practical implementation are discussed in detail. This approach has been applied very successfully to extract complete road networks from single SPOT scenes and aerial images. Thereby the algorithm runs in a monoplotting mode, deriving X, Y, Z coordinates of the roads, whereby the Z-component comes from real-time interpolation within an underlying DTM. Some experimental results are also given in this paper.

Citation Download Citation

Armin Gruen and Haihong Li "Semiautomatic road extraction by dynamic programming", Proc. SPIE 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision, (17 August 1994); https://doi.org/10.1117/12.182868

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