基于梯度融合的极化SAR图像引导滤波

doi:10.12305/j.issn.1001-506X.2025.09.11

系统工程与电子技术 ›› 2025, Vol. 47 ›› Issue (9): 2890-2904.doi: 10.12305/j.issn.1001-506X.2025.09.11

• 传感器与信号处理 • 上一篇

基于梯度融合的极化SAR图像引导滤波

李响¹(), 曾顶²(), 殷君君²^,*(), 国贤玉²(), 杨健³()

1. 北京无线电测量研究所，北京 100854
2. 北京科技大学计算机与通信工程学院，北京 100083
3. 清华大学电子工程系，北京 100084

收稿日期:2024-10-15 出版日期:2025-09-25 发布日期:2025-09-16
通讯作者: 殷君君 E-mail:150194353@qq.com;1215978653@qq.com;michelle198329@163.com;guoxianyu@xs.ustb.edu.cn;yangjian_ee@tsinghua.edu.cn
作者简介:李　响（1986—），男，高级工程师，博士，主要研究方向为极化识别
曾　顶（1998—），男，硕士，主要研究方向为极化SAR图像处理、极化SAR滤波
国贤玉（1991—），男，博士研究生，主要研究方向为雷达图像处理、雷达遥感
杨　健（1965—），男，教授，博士，主要研究方向为极化雷达信号处理
基金资助:
国家自然科学基金（62222102, 62171023）；中央高校基本科研业务费（FRF-TP-22-005C1）资助课题

Guided filtering for polarimetric SAR image based on gradient fusion

Xiang LI¹(), Ding ZENG²(), Junjun YIN²^,*(), Xianyu GUO²(), Jian YANG³()

1. Beijing Institute of Radio Measurement，Beijing 100854，China
2. School of Computer and Communication Engineering，University of Science and Technology Beijing，Beijing 100083，China
3. Department of Electronic Engineering，Tsinghua University，Beijing 100084，China

Received:2024-10-15 Online:2025-09-25 Published:2025-09-16
Contact: Junjun YIN E-mail:150194353@qq.com;1215978653@qq.com;michelle198329@163.com;guoxianyu@xs.ustb.edu.cn;yangjian_ee@tsinghua.edu.cn

摘要/Abstract

摘要：

在极化合成孔径雷达（synthetic aperture radar, SAR）图像的引导滤波降噪算法中，常见的方法都引入了非线性核函数，而忽略了优化引导图像的构造方法。对此，提出一种基于梯度融合的极化SAR引导滤波算法进行舰船数据降噪。对比不同梯度计算方法，利用优化后的似然比梯度获取舰船边缘梯度图像，通过图像二值化以及形态学操作获取到梯度信息和强度信息的融合图像，并将其作为引导图像对原极化SAR数据进行引导滤波。通过多幅SAR图像引导滤波降噪实验证明，所提算法能够解决SAR领域现有引导滤波中非线性核函数降噪效果不佳问题，其目测结果和数值指标优于改进Lee滤波以及非线性核函数引导滤波算法。

关键词: 极化合成孔径雷达, 引导滤波, 似然比梯度, 信息融合

Abstract:

In the guided filtering denoising algorithms for polarimetric synthetic aperture radar （SAR）, common methods typically introduce nonlinear kernel functions while neglecting the construction method of optimizing guidance image. In regard to this, a gradient fusion-based polarimetric SAR guided filtering algorithm is proposed for ship data denoising. It compares the different gradient computation methods and utilizes an optimized likelihood ratio gradient to obtain ship edge gradient images. By employing image binarization and morphological operations, the fused image of gradient information and intensity information is acquired and used as the guidance image to perform guided filtering on the original polarimetric SAR data. Multiple SAR images guided filtering denoising experiment demonstrate that the proposed algorithm can address the poor denoising performance of nonlinear kernel functions in existing guided filtering methods. Both visual results and numerical metrics indicate that the proposed algorithm outperforms the improved Lee filter and nonlinear kernel function guided filtering algorithms.

Key words: polarimetric synthetic aperture radar （SAR）, guided filtering, likelihood ratio gradient, information fusion

中图分类号:

TN 958

李响, 曾顶, 殷君君, 国贤玉, 杨健. 基于梯度融合的极化SAR图像引导滤波[J]. 系统工程与电子技术, 2025, 47(9): 2890-2904.

Xiang LI, Ding ZENG, Junjun YIN, Xianyu GUO, Jian YANG. Guided filtering for polarimetric SAR image based on gradient fusion[J]. Systems Engineering and Electronics, 2025, 47(9): 2890-2904.

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滤波类型	实验1			实验2
滤波类型	ENL	标准差	SSIM	ENL	标准差	SSIM
原始数据	1.1191	0.0772	1	1.2966	0.0777	1
改进Lee滤波	9.6233	0.0286	0.6088	9.2164	0.0292	0.5826
PNGF滤波	11.0304	0.0281	0.5660	10.4958	0.0279	0.5136
所提方法滤波	14.9783	0.0242	0.6436	13.3336	0.0251	0.6240

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基于梯度融合的极化SAR图像引导滤波

Guided filtering for polarimetric SAR image based on gradient fusion

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