基于双边滤波的极化SAR 相干斑抑制

基金项目:

国家自然科学基金(61173092, 61271302)，新世纪优秀人才支持计划(NCET-11-0692)，陕西省科学技术研究发展计划项目 (B07048)，以及教育部长江学者和创新团队发展计划(IRT1170)资助课题

Polarimetric SAR Speckle Reduction Based on Bilateral Filtering

(Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an 710071, China)

摘要: 在对极化SAR 数据进行相干斑抑制过程中，保持其极化信息是首要考虑的问题，而对极化SAR 数据各元素进行独立的滤波是不可取。依据极化SAR 数据形式及噪声模型，该文将双边滤波推广至极化SAR 数据处理，推导出一种新的相似性距离度量公式，所提方法可以直接对极化协方差矩阵C 或极化相干矩阵T 进行处理。该方法能够保持极化信息，有效地抑制相干斑，同时能够更好地保持点目标、纹理结构等，在处理大幅面的极化SAR数据时简单、快速、有效。
- 遥感图像 /
- 极化SAR(Pol-SAR) /
- 双边滤波 /
- 距离度量 /
- 协方差矩阵C
Abstract: The priority during speckle reduction in Polarimetric Synthetic Aperture Radar (Pol-SAR) data is to maintain the polarization information. For this reason, it is undesirable to separate each element of polarimetric SAR. Based on the multiplicative noise model and complex matrix, an effective distance similarity measure method is derived, which can process covariance matrix C or coherent matrix T directly. Experiments show that this method can effectively reduce speckle and maintain the polarization information, point targets, and texture structure. Moreover, it can handle large polarimetric SAR with simplicity and ease.
- Remote sensing image /
- Polarimetric SAR (Pol-SAR) /
- Bilateral filtering /
- Distance measure /
- Polarimetric covariance matrix C