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

Author

Cheng, Jianghua ; Ku, Xishu ; Liu, Jurong ; Guan, Yongfeng ; Sun, Jixiang

Author_Institution

Coll. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China

Volume

5

fYear

2010

fDate

27-29 March 2010

Firstpage

467

Lastpage

471

Abstract

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.

Keywords

edge detection; image classification; image resolution; image texture; pattern clustering; radar imaging; statistical analysis; synthetic aperture radar; automatic classification; best lag distance finding; built-up areas classification; edge detection; fuzzy c-mean clustering; geostatistical texture analysis; highresolution SAR images; semivariogram calculation; time consumption; Change detection algorithms; Clustering algorithms; Educational institutions; Image analysis; Image edge detection; Image texture; Image texture analysis; Markov random fields; Statistics; Sun; Built-up Areas Classification; Geostatistical Texture; SAR; Semivariogram;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Shenyang

Print_ISBN

978-1-4244-5845-5

Type

conf

DOI

10.1109/ICACC.2010.5487101

Filename

5487101