Journal of South China University of Technology (Natural Science Edition) ›› 2011, Vol. 39 ›› Issue (2): 60-64,70.doi: 10.3969/j.issn.1000.565X.2011.02.010

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Segmentation of SAR Images Based on NSCT and FCM Clustering

Sun Ji-feng  Deng Xiao-hui   

  1. South China university of technology, electronic and information institute, guangdong guangzhou 510640
  • Received:2010-05-31 Revised:2010-08-12 Online:2011-02-25 Published:2011-01-02
  • Contact: 孙季丰(1962-)，男，教授，主要从事通信系统信息处理、图像与视频处理研究 E-mail:ecjfsun@scut.edu.cn
  • About author:孙季丰(1962-)，男，教授，主要从事通信系统信息处理、图像与视频处理研究
  • Supported by:

    广东省自然科学基金资助项目(9151064101000037)

PDF

803

Abstract:

In order to realize the unsupervised and automatic segmentation of SAR（Synthetic Aperture Radar） ima-ges and improve the accuracy and computational efficiency of segmentation,a segmentation method of SAR images based on NSCT（Non-subsampled Contourlet Transform） and FCM（Fuzzy c-Means） clustering is proposed.In this method,first,a denoising method based on NSCT is used to preprocess SAR images,which may protect the details of texture information.Then,the gray and texture features of SAR images are extracted by an edge-preserving extraction method of gray feature and gray-level co-occurrence matrix.Finally,the improved method of fast determining the clustering number is combined with the FCM clustering algorithm to realize the automatic segmentation of SAR images.Experimental results show that the proposed method is precise and effective in the unsupervised and automatic segmentation of SAR images.

Key words: image segmentation, non-subsampled Contourlet transform, fuzzy c-means clustering