DocumentCode :
142606
Title :
Automated road extraction from multi-resolution images using spectral information and texture
Author :
Jianhua Wang ; Qiming Qin ; Xiucheng Yang ; Jun Wang ; Xin Ye ; Xuebin Qin
Author_Institution :
Inst. of remote sensing & GIS, Peking Univ., Beijing, China
fYear :
2014
fDate :
13-18 July 2014
Firstpage :
533
Lastpage :
536
Abstract :
Road is a kind of very typical artificial object. Road extraction from multi-scale remote sensing images is significant both in military field and in people´s daily lives. With the development of remote sensing technology, the scale of remote sensing images that can be obtained becomes various. Therefore, the research of multi-scale remote sensing images is getting more and more attention and it is really a challenging task in the field of image processing. In this paper, a method of road extraction from multi-scale remote sensing images is proposed. Firstly, the textures are extracted and added to the bands of the original image. The filtering, resampling and segmentation operations are then implemented. Next, the spectral characteristics and textures of roads on the remote sensing images are statistically analyzed, and the changes of those on multi-scale remote sensing images are obtained. Then, considering the road characteristics displayed on remote sensing images, some parameters of spectral characteristics and textures are selected to extract roads using the object-oriented method. Finally, the results of road extraction are post-processed based on the opening and closing operation of mathematical morphology. This study has great significance in areas such as features optimization, target recognition, building feature database and improving the utilization of remote sensing data.
Keywords :
feature extraction; geophysical image processing; image resolution; image segmentation; remote sensing; roads; artificial object; automated road extraction; features optimization; image filtering; image processing; image resampling; image segmentation; image spectral information; image texture; mathematical morphology; multiresolution images; multiscale remote sensing images; target recognition; Accuracy; Data mining; Feature extraction; Remote sensing; Roads; Spatial resolution; Multi-scale; Object-oriented; Road extraction; Spectral Characteristic; Texture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
Type :
conf
DOI :
10.1109/IGARSS.2014.6946477
Filename :
6946477
Link To Document :
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