• 学术论文 •

基于斑点统计特性保持的SAR影像迭代滤波

1. 辽宁工程技术大学测绘与地理科学学院遥感科学与应用研究所, 辽宁 阜新 123000
• 收稿日期:2020-11-16 修回日期:2021-04-07 出版日期:2021-10-21
• 作者简介:
• 李　玉　男, 1963年3月出生, 吉林省长春人. 现任辽宁工程技术大学教授、博士生导师. 主要研究方向为遥感数据处理理论与基础应用研究, 包括空间统计、随机几何、模糊数学在遥感数据建模与分析中的应用、目标几何与特征提取.E-mail: liyu@lntu.edu.cn
王姝运　女, 1994年11月出生, 河北省张家口人. 硕士. 主要研究方向为遥感图像处理. E-mail:761367857@qq.com
赵泉华　女, 1978年出生, 河北省承德人, 现任辽宁工程技术大学教授、博士生导师. 主要研究方向为遥感图像建模与分析以及随机几何在遥感图像中的应用. E-mail:zqhlby@163.com
• 基金资助:
• 国家自然科学基金青年基金项目 (41801233)

Iterative Filtering of SAR Image Based on Speckle Statistical Characteristic Preservation

LI Yu, WANG Shu-yun, ZHAO Quan-hua

1. Institute for Remote Sensing Science and Application, School of Geomatics, Liaoning Technical University, Fuxin, Liaoning 123000, China
• Received:2020-11-16 Revised:2021-04-07 Online:2021-10-21 Published:2021-09-25
• Supported by:
• Youth Fund of National Natural Science Foundation of China (41801233)

Abstract:

The speckle phenomenon in synthetic aperture radar (SAR) images is caused by the mutual interference of backscattering signals of ground objects. Although it is similar to noise, it involves the scattering characteristics of ground objects. The scattering characteristics of the same ground object can be described by the speckle statistical distribution model. Therefore, in the process of noise reduction, the scattering information of the ground object contained in the speckle can be preserved by restoring the statistical distribution characteristics of speckle. Based on this idea, an iterative filtering method of SAR image based on speckle statistical characteristic preservation is proposed. The proposed method assumes that the statistical distribution function of a given SAR image is known a priori, namely the mixture Gamma distribution, and its distribution parameters can be estimated by the pixel values of the image. Then, the EM（Expectation Maximization） algorithm is used to segment the SAR image based on the mixture Gamma distribution, so as to obtain the homogeneous regions in the image. Subsequently, for different homogeneous regions, select the gray levels with larger fitting errors, calculate the densities of the pixels whose values are the gray levels according to the segmentation results, and judge whether they are abnormal pixels, and the abnormal pixels are filtered by Frost filter. Repeat above procedure until the histogram of filtered image fits the statistical distribution function well. Experimental results of GF-3 and Radarsat-2 SAR image show that, on the premise of maintaining image quality, the proposed method can not only obtain better statistical modeling results, but also suppress speckle well and achieve image denoising.