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Proceedings Paper

Road extraction based on Scansnake from Beijing-1 image
Author(s): Jianming Gong; Xiaomei Yang; Min Wang; Jian Lu; Dandan Zhang
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Paper Abstract

Beijing-1 small satellite image of 4m high resolution not only makes it possible to extract the detailed information that is difficult to be obtained from low-resolution images, but also brings out new research subjects for automatic extraction and identification of thematic information. The reason for this are as follows:(1) the obvious increase of data requires higher spatial and temporal efficiency of image data retrieval, display, processing, etc.; (2) due to the highly detailed information of high resolution image, under the influence of the Bidirectional Reflectance Distribution Function (BRDF), different parts of the same object may have different grey levels; together with factors such as object shadow, mutual cover, and cloud cover, the phenomenon of same object, different spectrum of high resolution images becomes more prominent, and the different object, same spectrum still exists, which brings greater difficulties to the work of information extraction [1][2]. The road of high resolution image has the following features: (1) the width of the road varies slightly and slowly; (2) the direction of the road varies slowly; (3) the local mean grey level of the road varies slowly; (4) the road is relatively long. Due to the increase of the resolution, the noises such as bridges, cars and trees along the road and its edge also increase. The paper proposes a new road extraction algorithm namely Scansnake aimed at the features of Beijing-1 images. A large amount of experiments proved that Scansnake algorithm has the advantage of object tracking, and under a series of complex conditions such as the variation of the width of the road and the change of grey feature distribution, Scansnake method can extract the road information of the high resolution Beijing-1 image

Paper Details

Date Published: 15 November 2007
PDF: 9 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861W (15 November 2007); doi: 10.1117/12.748981
Show Author Affiliations
Jianming Gong, Wuhan Univ. (China)
State Key Lab. of Resources and Environmental Information Systems (China)
Xiaomei Yang, State Key Lab. of Resources and Environmental Information Systems (China)
Min Wang, Nanjing Normal Univ. (China)
Jian Lu, Wuhan Univ. (China)
Dandan Zhang, State Key Lab. of Resources and Environmental Information Systems (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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