Paper
30 October 2009 Road extraction from high-resolution remote sensing images based on spectral and shape features
Kun Wang, Dongping Ming
Author Affiliations +
Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74953R (2009) https://doi.org/10.1117/12.833184
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
Abstract
Road extraction from high-resolution remote sensing images has always been a significant but very difficult task. In this paper, a new approach integrating spectral and shape features into the object extraction process is proposed. The method mainly consists of three modules: spectral classification, morphological segmentation and shape feature recognition. The principal work is to refine the road network using three shape indices (distribution density, eccentricity and precision), which can remove the spectrally similar non-road objects. Experimental results demonstrate that this method is efficient to extract the central road network.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kun Wang and Dongping Ming "Road extraction from high-resolution remote sensing images based on spectral and shape features", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74953R (30 October 2009); https://doi.org/10.1117/12.833184
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Roads

Image segmentation

Feature extraction

Buildings

Remote sensing

Image classification

Image fusion

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