A Fast and Automatic Algorithm for Built-up Areas Classification in High-Resolution SAR Images Based on Geostatistical Texture

摘要：

Nowadays, main methods used to SAR imagery built-up areas classification are GLCM (gray-level cooccurrence 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.

关键词： SAR Built-up Areas Classification Geostatistical Texture Semivariogram.

作者: Jianghua Cheng Xishu Ku Jurong Liu Yongfeng Guan Jixiang Sun

作者单位: College of Electronic Science and Engineering National University of Defense Technology

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 467-471

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）