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A fast and automatic algorithm for built-up areas classification in high-resolution SAR images based on geostatistical texture

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5 Author(s)
Jianghua Cheng ; Coll. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China ; Xishu Ku ; Jurong Liu ; Yongfeng Guan
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Nowadays, main methods used to SAR imagery built-up areas classification are GLCM (gray-level co-occurrence matrix) textural analysis, Markov random field, etc. They are extraordinarily time consumption and need for manual interaction. In this paper, a new scheme for fast and automatic classification of built-up areas is presented. It is based on geostatistical texture analysis and mainly consists of four parts: semivariogram calculation, best lag distance finding, FCM (Fuzzy C-Mean) clustering, and edge detection. The experimental results show that it is robust, fast and accurate.

Published in:

Advanced Computer Control (ICACC), 2010 2nd International Conference on  (Volume:5 )

Date of Conference:

27-29 March 2010