J4 ›› 2015, Vol. 42 ›› Issue (3): 148-153+204.doi: 10.3969/j.issn.1001-2400.2015.03.025

• 研究论文 • 上一篇    下一篇

PolSAR快速贝叶斯非局部均值相干斑抑制方法

陈建宏1;赵拥军1;时银水2;刘伟1   

  1. (1. 信息工程大学 导航与空天目标工程学院,河南 郑州  450001;
    2. 防空兵学院 侦察预警系,河南 郑州  450052)
  • 收稿日期:2014-04-15 出版日期:2015-06-20 发布日期:2015-07-27
  • 通讯作者: 陈建宏
  • 作者简介:陈建宏(1980-),男,工程师,信息工程大学博士研究生,E-mail:gycjh2010@163.com.
  • 基金资助:

    国家自然科学基金资助项目(41301481, 61302160)

Fast Bayesian non-local means of polarimetric  SAR image despeckling

CHEN Jianhong1;ZHAO Yongjun1;SHI Yinshui2;LIU Wei1   

  1. (1. School of Navigation and Aerospace Engineering, Information Engineering Univ., Zhengzhou  450001,  China;
    2. Dept. of Reconnaissance & Early Warning, Air Defense College, Zhengzhou  450052, China)
  • Received:2014-04-15 Online:2015-06-20 Published:2015-07-27
  • Contact: CHEN Jianhong

摘要:

从单极化合成孔径雷达(SAR)贝叶斯非局部均值算法出发,推导了极化相干矩阵在复Wishart分布下的块相似性度量函数,给出了无先验知识下的极化SAR贝叶斯非局部均值模型,并采用积分图实现了该算法的快速计算.最后,通过机载合成孔径雷达实测旧金山地区的极化SAR数据进行了验证.实验结果表明,文中方法能够有效抑制相干斑的同时,保持了极化特征,并大幅提升了运算效率.

关键词: 合成孔径雷达, 极化, 相干斑, 非局部均值, 贝叶斯

Abstract:

Based on the Bayesian non-local means of the single polarization SAR, block similarity measurement of the polarimetric coherence matrix is derived by combining with the polarimetric coherence matrix adhering to complex Wishart distribution. The polarimetric SAR Bayesian non-local means model is given without prior knowledge. Then its fast algorithm is realized using the integral image. Finally, we verify the proposed algorithm with a full polarimetric image from AIRSAR to San Francisco district. Experimental results from real Polarimetric SAR data show that the proposed algorithm not only despeckes effectively but also preserves polarimetric information well. Besides, computing efficiency is improved greatly.

Key words: synthetic aperture radar, polarization, speckle, non-local means, Bayesian

中图分类号: 

  • TP75