›› 2011, Vol. 24 ›› Issue (11): 66-.

• 论文 • 上一篇    下一篇

基于灰度共生矩的SAR图像纹理特征提取方法

杨凯陟,程英蕾   

  1. (空军工程大学 电讯工程学院,陕西 西安 710077)
  • 出版日期:2011-11-15 发布日期:2011-11-25
  • 作者简介:杨凯陟(1990—),男,硕士研究生。研究方向:数字图像处理。程英蕾(1964—),女,博士,教授。研究方向:多传感器图像处理和模式识别。
  • 基金资助:

    陕西自然科学基金资助项目(2010JM8038)

A Method of SAR Image Texture Feature Extraction Based on Co-occurrence Matrix

 YANG Kai-Zhi, CHENG Ying-Lei   

  1. (School of Telecommunications Engineering,Air Force Engineering University,Xi'an 710077,China)
  • Online:2011-11-15 Published:2011-11-25

摘要:

为更有效地提取合成孔径雷达(SAR)图像中的有效信息,提出了一种基于灰度共生矩阵的纹理特征提取方法。该方法在分析图像灰度共生矩常用特征描述量基础上,研究了窗口尺寸和位移向量对纹理特征的影响,通过比较不同目标各种纹理特征的分布及平均值的相差程度,计算了灰度共生矩阵的最佳窗口尺寸和位移向量,确定参与分类的可用纹理特征组合,给出了特征选择和提取方法。实验结果显示,该方法提取的特征具有较好的目标描述效果。

关键词: SAR图像, 纹理特征, 灰度共生矩阵, 特征提取

Abstract:

To extract available information from SAR images effectively,this paper proposes a method of texture feature extraction based on co-occurrence matrix.This paper first analyzes the common attribute values of co-occurrence matrix and the influence of window size and displacement vector on texture feature.By comparing the distribution and mean value of different objects' texture,it obtains the best window size and displace vector used to calculate co-occurrence matrix,and determines practicable texture feature combination for classification.Finally,this paper gives methods for texture feature selection and extraction.The experiment results show that the features extracted by the method are effective in describing objects.

Key words: SAR image;texture feature;co-occurrence matrix;feature extraction

中图分类号: 

  • TN958