A Despeckling Algorithm for Synthetic Aperture Radar Images Using Region Subdivision

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A Despeckling Algorithm for Synthetic Aperture Radar Images Using Region Subdivision

更新时间：2025-07-09

- A Despeckling Algorithm for Synthetic Aperture Radar Images Using Region Subdivision
- Vol. 46, Issue 10, Pages: 83-88(2012)
- 作者机构：
  
  1. 西安电子科技大学雷达信号处理国家重点实验室,西安,710071
  2. 西安工程大学电子信息学院,西安,710048
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.73
- Online First：10 October 2012，
  
  Published：2012
- 稿件说明：
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A Despeckling Algorithm for Synthetic Aperture Radar Images Using Region Subdivision[J]. 2012, 46(10): 83-88.
DOI：

A Despeckling Algorithm for Synthetic Aperture Radar Images Using Region Subdivision[J]. 2012, 46(10): 83-88. DOI：

摘要

为在有效保护合成孔径雷达(SAR)图像边缘特征的同时进一步提高乘性相干斑噪声的抑制性能

提出了一种基于区域划分的SAR图像相干斑抑制(DABRS)算法.首先利用带方向的高斯-伽马平行窗通过比率运算生成边缘强度映射(ESM)

并利用阈值化ESM对SAR图像进行区域划分

然后利用改进的变窗Kuan滤波与改进的Sigma滤波分别对SAR图像的均匀区域与边缘区域进行相干斑抑制.为进一步提高抑斑效果

两种改进抑斑算法均采用迭代滤波方式

且改进Kuan滤波的窗尺度随迭代次数的增加而增大.实验结果表明:与多种抑斑算法相比

DABRS算法在抑斑与边缘保护方面具有优势

等效视数提高超过30%

边缘保持指数提高8%以上

而且抑斑图像同质区还具有更平滑的视觉效果.

Abstract

A new despeckling algorithm based on region subdivision(DABRS)is presented to effectively preserve edge characteristics and to improve the performance of reducing multiplicative speckle noise in synthetic aperture radar(SAR). Gaussian-Gamma-shaped bi-windows with different orientations are used to obtain the edge strength map(ESM)by ratio operations. Then

the threshold-processing ESM is used to divide a SAR image into different regions. Two improved filters

the Kuan filter with variable-size windows and the Sigma filter

are used to reduce speckle in homogeneous and edge regions

respectively. Iteration filtering strategy is adopted by the two improved filters to smooth speckle better

and the window size of improved Kuan filter increases with iteration progressing. Experimental results and comparisons with most existing despeckling algorithms show that the DABRS has advantages in the speckle suppression and edge preservation

improves the equivalent number of looks by more than 30%

increases the edge keep index by more than 8%

and has more smooth visual effects in the homogeneous regions of despeckling images.

关键词

Keywords

references

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BUEMI M E, JACOBO J, MEJAIL M. SAR image processing using adaptive stack filter [J]. Pattern Recognition Letters, 2010, 31(4): 307-314.

BIANCHI T, ARGENTI F, ALPARONE L. Segmentation-based MAP despeckling of SAR images in the undecimated wavelet domain [J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(9): 2728-2742.

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凤宏晓,侯彪,焦李成,等. 基于非下采样Contourlet域局部高斯模型和MAP的SAR图像相干斑抑制[J].电子学报,2010,38(4):811-816.

FENG Hongxiao, HOU Biao, JIAO Licheng, et al. SAR image despeckling based on local Gaussian model and MAP in NSCT domain [J]. Acta Electronica Sinica, 2010, 38(4): 811-816.

贾建,陈莉. 基于双变量模型和非下采样Contourlet变换的SAR图像相干斑抑制[J]. 电子与信息学报, 2011,33(5):1088-1094.

JIA Jian,CHEN Li. SAR image despeckling based on bivariate threshold function in NSCT domain[J]. Journal of Electronics Information Technology, 2011, 33(5):1088-1094.

YU Y, ACTON S. Speckle reducing anisotropic diffusion[J]. IEEE Transactions on Image Processing, 2002, 11(11): 1260-1270.

LIU Guojin, ZENG Xiaoping, TIAN Fengchun, et al. Speckle reduction by adaptive window anisotropic diffusion [J]. Signal Processing, 2009, 89: 2233-2243.

JESPER S, HENNING S, ALLAN A, et al. CFAR edge detection for polarimetric SAR images [J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(1): 20-32.

SHUI Penglang, CHEN Dong. Edge detector of SAR images using Gaussian gamma shaped bi-windows [J]. IEEE Geoscience and Remote Sensing Letters, 2012, 9(5): 846-850.

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