Study on Optimal Segmenting Scale of Grassland in Remote Sensing Objects

Abstract:

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Determining optimal segmenting scale of remote sensing objects is very important for remote sensing classification and identification. At present, selecting the optimal scales for objects in remote sensing images usually uses two methods, that is, average local variance and maximum area. Due to influences of subjective factors and difficult to implement, this paper proposes a new method based on fractal dimension to solve this problem. This experiment probes certain internal connections between fractal dimension on different scale and optimal segmenting scale of remote sensing objects. It offers a new method for seeking efficient ways to determine optimal scales of different objects in remote sensing images

Info:

Periodical:

Advanced Materials Research (Volumes 171-172)

Edited by:

Zhihua Xu, Gang Shen and Sally Lin

Pages:

240-245

DOI:

10.4028/www.scientific.net/AMR.171-172.240

Citation:

W. Cui and Q. Q. Li, "Study on Optimal Segmenting Scale of Grassland in Remote Sensing Objects", Advanced Materials Research, Vols. 171-172, pp. 240-245, 2011

Online since:

December 2010

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Price:

$35.00

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