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Proceedings Paper

Wetland information extraction of remote sensing imagery based on Markov random field theory
Author(s): Dengrong Zhang; Yang Wu
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Paper Abstract

Due to the indistinction of land boundary and the confusion of categories in wetland as well as the big spectral difference of high-resolution remote sensing images, how to segment land boundaries exactly and maintain homogeneity in one category as much as possible are the difficult points of wetland information extraction of remote sensing images. In this paper, Xixi Wetland in Hangzhou is taken as research object and QuickBird high-resolution image as research data. Two approaches for wetland information accurate extraction based on Markov random field (MRF) theory are explored. The experimental results showed that this method has a good effect on exact segmentation of land boundaries and Inhibition of classification noises, and has higher accuracy and speed compared with other MRF methods.

Paper Details

Date Published: 15 August 2011
PDF: 8 pages
Proc. SPIE 8203, Remote Sensing of the Environment: The 17th China Conference on Remote Sensing, 820318 (15 August 2011); doi: 10.1117/12.910425
Show Author Affiliations
Dengrong Zhang, Hangzhou Normal Univ. (China)
Yang Wu, Zhejiang Univ. (China)


Published in SPIE Proceedings Vol. 8203:
Remote Sensing of the Environment: The 17th China Conference on Remote Sensing
Qingxi Tong; Xingfa Gu; Boqin Zhu, Editor(s)

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