Linear Optimal Filter with Minimum Mean Square Error for Synthetic Aperture Radar Images

您当前的位置：

首页 >

文章列表页 >

Linear Optimal Filter with Minimum Mean Square Error for Synthetic Aperture Radar Images

更新时间：2025-07-09

- Linear Optimal Filter with Minimum Mean Square Error for Synthetic Aperture Radar Images
- Vol. 43, Issue 12, Pages: 6-10(2009)
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP753
- Online First：10 December 2009，
  
  Published：2009
- 稿件说明：
移动端阅览
Linear Optimal Filter with Minimum Mean Square Error for Synthetic Aperture Radar Images[J]. 2009, 43(12): 6-10.
DOI：

Linear Optimal Filter with Minimum Mean Square Error for Synthetic Aperture Radar Images[J]. 2009, 43(12): 6-10. DOI：

摘要

针对常用于合成孔径雷达(SAR)图像降噪的Lee滤波和Kuan滤波误差较大的问题

提出了基于最小均方误差(MMSE)准则的线性最优滤波.线性最优滤波通过把斑点噪声的乘性模型同时展开为一阶和二阶泰勒级数

然后使用MMSE准则获得线性滤波的统一模型

最后再对该统一模型使用MMSE准则而获得.线性最优滤波在所有的线性滤波中具有最低的滤波误差

因而具有最高的滤波精度.对某乡村和城区SAR图像的降噪实验表明:线性最优滤波对边缘细节的保留能力强于Kuan滤波

它对斑点噪声的滤除能力强于Lee滤波; 与最大后验概率(MAP)滤波相比

线性最优滤波虽然具有较弱的边缘细节保留能力

但它对斑点噪声的滤除能力却强于MAP滤波.

Abstract

A linear optimal filter is proposed based on the minimum mean square error(MMSE)criterion to solve the problem that the commonly used Lee and Kuan filters for synthetic aperture radar(SAR)images have bigger filtering errors. The multiplicative noise model of speckle is expanded into both the first-order and the second-order Taylor series at the same time

and then the MMSE criterion is used to deduce a unified model of linear filters. The linear optimal filter is finally obtained-by applying the MMSE criterion again to the unified model. The linear optimal filter has the lowest filtering error and the highest filtering accuracy among all linear filters. The despeckling experiments on rural and urban SAR images show that the linear optimal filter has higher edge and fine detail preserving capacity than the Kuan filter

and has higher speckle suppression than the Lee filter. A comparison with the maximum a posteriori filter shows that the linear optimal filter has lower edge and fine detail preserving capacity

but has higher capability of speckle suppression.

关键词

Keywords

references

皮亦鸣, 杨建宇,付毓生,等. 合成孔径雷达成像原理[M]. 成都: 电子科技大学出版社, 2007.

MAITRE H. 合成孔径雷达图像处理[M]. 孙洪, 译. 北京: 电子工业出版社, 2005.

LOPES A, TOUZI R, NEZRY E. Adaptive speckle filters and scene heterogeneity [J]. IEEE Transactions on Geoscience and Remote Sensing, 1990, 28(6): 992-1000.

FERNANDEZ S A, LOPEZ C A. On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering [J]. IEEE Transactions on Image Processing, 2006, 15(9): 2694-2701.

LEE J S, GRUNES M R, SCHULER D L, et al. Scattering-model-based speckle filtering of polarimetric SAR data [J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(1): 176-187.

KUAN D T, SAWCHUK A A, STRAND T C, et al. Adaptive restoration of images with speckle [J]. IEEE Transactions on Acoustics, Speech, Signal Processing, 1987, 35(3): 373-383.

TOUZI R. A review of speckle filtering in the context of estimation theory [J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11): 2392-2404.

LEE J S. Speckle suppression and analysis for synthetic aperture radar images [J]. Optical Engineering, 1986, 25(5): 636-643.

ACHIM A, KURUOGLU E E. Image denoising using bivariate alpha-stable distributions in the complex wavelet domain [J]. IEEE Signal Processing Letters, 2005, 12(1): 17-20.

ACHIM A, KURUOGLU E E, ZERUBIA J. SAR image filtering based on the heavy-tailed Rayleigh model [J]. IEEE Transactions on Image Processing, 2006, 15(9): 2686-2693.

SOLBO S, ELTOFT T. Γ-WMAP: a statistical speckle filter operating in the wavelet domain [J]. International Journal of Remote Sensing, 2004, 25(5): 1019-1036.

一种处理边缘不连续图像的雷达算法.西安交通大学学报, 2005, 39(12):1331-1135.

基于粗集理论的雷达辐射源信号识别.西安交通大学学报, 2005, 39(8):871-875.

合成孔径雷达图像中机场跑道的自动识别.西安交通大学学报, 2004, 38(12):1243-1246.

基于UML的软件可靠性测试用例生成的混合模型. 西安交通大学学报, 2007, 41(4):421-425.

高速运动目标的频域合成带宽方法. 西安交通大学学报, 2007, 41(10):1184-1187.

斜视干涉逆合成孔径雷达成像算法. 西安交通大学学报, 2008, 42(10):1290-1294.

一种精确估计恒虚警检测器阈值因子的方法. 西安交通大学学报, 2009, 43(2):67-71.

采用Radon模糊变换的宽带雷达多目标检测方法. 西安交通大学学报, 2009, 43(4):85-89.

地面运动目标不模糊径向速度估计的方法. 西安交通大学学报, 2009, 43(8):76-79.

适合于小波视频编码的尺寸自适应图像组结构. 西安交通大学学报, 2009, 43(4): 52-56.

基于等高线的图像特征表达. 西安交通大学学报, 2008, 42(4):385-388.

一种医学X射线图像动态范围扩展方法. 西安交通大学学报, 2008, 42(12):1468-1471.

一种轮廓变化图像小波矩的步态识别. 西安交通大学学报, 2009, 43(1):90-94.

利用贫富差距原理进行图像边缘检测. 西安交通大学学报, 2009, 43(4):44-48.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

A Despeckling Algorithm for Synthetic Aperture Radar Images Using Region Subdivision

Numerical Simulation of the Energy Conversion Process in Thermoacoustic Engines with Different Stack Materials

A Fast Calculation Method for Thermal Flow Fields in Transformer Windings Based on PI-DeepONet

Integrated and Joint Design Optimization of Centrifugal Compressor Impeller and Casing Treatment at Multiple Working Points

Influence of Structural Parameters on the Summer Operational Characteristics of a Three-Tower-in-One Indirect Air-Cooling System

Related Author

朱磊 1

水鹏朗 1

章为川 1

周忠根 1

Related Institution

National Key Laboratory of Radar Signal Processing, Xidian University

Electronics and Information College, Xi'an Polytechnic University

⁰