电子与自动控制

基于信息论匀质性测度的各向异性扩散相干斑抑制算法

  • 何友 ,
  • 袁湛 ,
  • 蔡复青
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  • 海军航空工程学院 信息融合技术研究所, 山东 烟台 264001
何友,男,博士,教授,博士生导师。主要研究方向:信息融合、雷达信号检测与估计。Tel:0535-6635695,E-mail:yxgx@sina.com;袁湛,男,博士研究生。主要研究方向:雷达信号检测与估计、SAR图像处理。Tel:0535-6635695,E-mail:yuanzhan_com@yahoo.com.cn;蔡复青,男,博士,讲师。主要研究方向:双基地SAR成像算法。Tel:0535-6635695,E-mail:cfq197404@163.com

收稿日期: 2012-02-13

  修回日期: 2012-05-18

  网络出版日期: 2013-01-19

基金资助

国家自然科学基金(61032001,61002045)

Speckle Suppression Using Anisotropic Diffusion Based on Information-theoretic Heterogeneity Measurement

  • HE You ,
  • YUAN Zhan ,
  • CAI Fuqing
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  • Research Institute of Information Fusion Technology, Naval Aeronautical and Astronautical University, Yantai 264001, China

Received date: 2012-02-13

  Revised date: 2012-05-18

  Online published: 2013-01-19

Supported by

National Natural Science Foundation of China (61032001,61002045)

摘要

针对传统各向异性扩散抑斑算法存在的均匀区域噪声平滑不充分、边缘随迭代弱化及迭代次数的确定缺乏理论指导等问题,提出了一种新的各向异性扩散抑斑算法,该算法采用信息论匀质性测度作为图像中匀质区域与边缘的鉴别因子,使扩散系数能够更准确地控制扩散强度与扩散速率,从而达到充分平滑均匀区域噪声及保护边缘的目的。基于各向异性扩散方程求解与鲁棒误差范数最小化的等效性,提出了一种各向异性扩散方程的迭代停止准则。利用合成孔径雷达图像对本文算法的抑斑和边缘保持性能进行了仿真实验验证。结果表明,本文算法在均匀区域相干斑噪声抑制、边缘保持等方面均取得了优于传统算法的效果。

本文引用格式

何友 , 袁湛 , 蔡复青 . 基于信息论匀质性测度的各向异性扩散相干斑抑制算法[J]. 航空学报, 2013 , 34(1) : 153 -163 . DOI: 10.7527/S1000-6893.2013.0018

Abstract

Current speckle reduction anisotropic diffusion algorithms cannot adequately smooth the speckle noise in homogeneous areas and make the edges blurred as the number of iteration increases. A novel speckle reduction anisotropic diffusion algorithm is proposed in this paper based on information-theoretic heterogeneity measurement which can effectively discriminate the homogeneous area and the edge area. With this useful property of the information-theoretic heterogeneity measurement, the diffusion coefficient can better control the diffusion strength and the speed to fully suppress the speckle noise and meanwhile preserve the edges. Based on the equivalence of solving the anisotropic diffusion equation and minimizing the robust error norm, a stopping iteration criterion is designed for the anisotropic diffusion equation. Synthetically speckled and real synthetic aperture radar images are utilized to test the smoothing performance and the ability to preserve edges of the proposed algorithm, and the experimental results show its efficiency and superiority over the traditional algorithms.

参考文献

[1] Lee J S. Digital image enhancement and noise filtering by use of local statistics. IEEE Transactions on Pattern Analysis Machine Intelligence, 1980, 2(2): 165-168.
[2] Baraldi A, Parmigiani F. A refined Gamma MAP SAR speckle filter with improved geometrical adaptivity. IEEE Transactions on Geoscience and Remote Sensing, 1995, 33(5): 1245-1257.
[3] Donoho D L. De-niosing by soft-thresholding. IEEE Transaction on Information Theory, 1995, 44(3): 613-627.
[4] Foucher S, Benie G B, Boucher J M. Multiscale MAP filtering of SAR images. IEEE Transactions on Image Processing, 2001, 10(1): 49-60.
[5] Dusan G, Mihai D. Wavelet-based despeckling of SAR images using Gauss-Markov random fields. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(12):4127-4143.
[6] Min D, Cheng P, Andrew K C, et al. Bayesian wavelet shrinkage with edge detection for SAR image despeckling. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(8): 1642-1648.
[7] Pietro P, Jitendra M. Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(7): 629-639.
[8] Yu Y J, Acton S T. Speckle reducing anisotropic diffusion. IEEE Transactions on Image Processing, 2002, 11(11): 1260-1270.
[9] Santiago A F, Carlos A L. On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering. IEEE Transactions on Image Processing, 2006, 15(9): 2694-2701.
[10] Yu J H, Wang Y Y, Shen Y Z. Noise reduction and edge detection via kernel anisotropic diffusion. Pattern Recognition Letters,2008,29(10): 1496-1503.
[11] You Y L, Xu W Y, Tannenbaum A, et.al. Behavioral analysis of anisotropic diffusion in image processing. IEEE Transactions on Image Processing, 1996, 5(11): 1539- 1553.
[12] Aiazzi B, Alparone L, Baronti S. Information-theoretic heterogeneity measurement for SAR imagery. IEEE Transactions on Geoscience and Remote Sensing, 2004, 43(3): 619-624.
[13] Ulaby F T, Kouyate F, Brisco B, et al. Texture information in SAR images. IEEE Transactions on Geoscience and Remote Sensing, 1986, 24(2): 235-245.
[14] Beauchemin M, Thomoson K P B, Edwards G. The ratio of the arithmetic to the geometric mean: a first-order statistical test for multilook SAR image homogeneity. IEEE Transactions on Geoscience and Remote Sensing, 1996, 34(2): 604-606.
[15] Oliver C, Quegan S. Understanding synthetic aperture radar images. London: Artech House, 1998.
[16] Black M J, Sapiro G, Mairmont D H, et al. Robust anisotropic diffusion. IEEE Transactions on Image Processing, 1998, 7(3): 421-432.
[17] Chen S B, Liu J G, Wang G Y, et al. SAR image heterogeneity and speckle filtering. Electronics Letters, 2010, 46(1): 80-82.
[18] Pratt W K. Digital image processing. New York: Wiley, 1978.
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