航空学报 > 2006, Vol. 27 Issue (5): 928-933

利用α稳定分布的小波域SAR图像降斑算法

胡正磊, 孙进平, 袁运能, 毛士艺   

  1. 北京航空航天大学 203教研室, 北京 100083
  • 收稿日期:2005-06-02 修回日期:2005-10-09 出版日期:2006-10-25 发布日期:2006-10-25

SAR Image Despeckling in Wavelet Domain Based on α-Stable Model

HU Zheng-lei, SUN Jin-ping, YUAN Yun-neng, MAO Shi-yi   

  1. Faculty 203, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
  • Received:2005-06-02 Revised:2005-10-09 Online:2006-10-25 Published:2006-10-25

摘要: 提出了一种改进的合成孔径雷达(SAR)图像α-MAP降斑算法,通过采用厚尾α稳定分布和引入噪声方差调整系数的方法,可以获得更好的降斑和纹理保持效果,同时应用平稳小波分解来解决Gibbs效应引入的伪噪声问题。最后通过对实际SAR图像的降斑处理,对本文的算法与最新的小波软阈值算法以及传统的局部自适应滤波器在性能参数和滤波效果上做了全面的比较。试验表明本文的算法更具适应性,实现了降斑与纹理保持更有效的综合滤波,在性能参数和复原图像效果上都有较好的表现。

关键词: SAR图像降斑, 小波分析, 对称α稳定分布, MAP估计

Abstract: An improved maximum a posteriori (MAP) estimator based on the heavy-tailed alpha-stable distribution is proposed. This method performs better in both speckle reduction and feature preservation, since the alpha-distribution model is used and a coefficient depending on the variance of the noise is introduced. Besides, the stationary wavelet transform (SWT) is used to avoid the artifacts as a result of Gibbs phenomenon. Finally, the proposed method is compared with the current state-of-the-art soft thresholding techniques and other local statistics filters applied on real SAR image and the proposed method is confirmed to be more adaptive, and it performs more effective in terms of both quantitive parameters and reconstructive image.

Key words: SAR image despeckling, wavelet analysis, symmetric alpha-stable distribution, MAP estimation

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