Paper
26 October 2013 Extracting roads from remote sensing images with the aid of path morphology and parallelized graph cuts
Author Affiliations +
Proceedings Volume 8918, MIPPR 2013: Automatic Target Recognition and Navigation; 89180H (2013) https://doi.org/10.1117/12.2030824
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
Abstract
While Graph Cuts are used for image segmentation, there exist two problems: how to get better initial information of foreground and background and how to improve the executing efficiency of Graph Cuts algorithm. To solve the first problem, path morphology and line segment matching algorithm are performed to get initial background information at the same time as getting initial foreground information, so non-road pixels similar with road pixels in gray value or texture are avoided being segmented as road points. To cope with the second problem, push-relabel strategy is chosen and its parallelized version based on NVIDIA CUDA platform is performed in this paper. Our strategy is performed on dense built-up area and suburban district and proved to be effective in both accuracy and efficiency.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhulin Zhang and Shaoguang Zhou "Extracting roads from remote sensing images with the aid of path morphology and parallelized graph cuts", Proc. SPIE 8918, MIPPR 2013: Automatic Target Recognition and Navigation, 89180H (26 October 2013); https://doi.org/10.1117/12.2030824
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Roads

Image segmentation

Remote sensing

Image processing algorithms and systems

Buildings

Image resolution

Algorithm development

RELATED CONTENT


Back to Top