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小波模拟退火-软阈值SAR图像降噪算法

周荫清 张磊 徐华平

周荫清, 张磊, 徐华平等 . 小波模拟退火-软阈值SAR图像降噪算法[J]. 北京航空航天大学学报, 2006, 32(03): 293-296.
引用本文: 周荫清, 张磊, 徐华平等 . 小波模拟退火-软阈值SAR图像降噪算法[J]. 北京航空航天大学学报, 2006, 32(03): 293-296.
Zhou Yinqing, Zhang Lei, Xu Huapinget al. Combined simulated annealing and soft-threshold wavelet de-noising of SAR image[J]. Journal of Beijing University of Aeronautics and Astronautics, 2006, 32(03): 293-296. (in Chinese)
Citation: Zhou Yinqing, Zhang Lei, Xu Huapinget al. Combined simulated annealing and soft-threshold wavelet de-noising of SAR image[J]. Journal of Beijing University of Aeronautics and Astronautics, 2006, 32(03): 293-296. (in Chinese)

小波模拟退火-软阈值SAR图像降噪算法

详细信息
    作者简介:

    周荫清(1936-),男,湖南湘潭人,教授,buaazyq@263.net.

  • 中图分类号: TN 957

Combined simulated annealing and soft-threshold wavelet de-noising of SAR image

  • 摘要: 提出了一种新的SAR(Synthetic Aperture Radar)图像降噪方法,利用小波变换对空间位置信息保留的特性,依据小波变换后近似图像仍满足吉布斯分布,将模拟退火算法引入到小波域中,首先,根据SAR功率图像斑点的特性,对传统的同态变换方法做出了相应的修正,大大降低了处理结果的辐射偏差,提高了等效视数,然后在多分辨率理论和小波变换理论基础上,选用适合特定图像的最优小波基进行分解,最后对小波变换后的近似图像进行模拟退火处理,对各个细节图像有选择地进行软阈值处理.实验证明,此方法比传统的小波降斑取得了更好的平滑效果,比传统模拟退火大大减少了处理的时间,同时对图像的辐射精度的保持,斑点的抑制,以及边缘保持都有较满意的结果.

     

  • [1] Lee J S. Simple speckle smoothing algorithm for synthetic aperture radar images[J]. IEEE Transactions on Systems, Man and Cybernetics, 1983, 13(1):85~89 [2] 李春升. 高分辨率星载SAR单视图像斑点噪声抑制实现方法[J]. 电子学报,2000, 28(3):13~16 Li Chunsheng. Speckle reduction for high resolution one-look spaceborne SAR images[J]. Acta Electronica Sinica, 2000, 28(3):13~16(in Chinese) [3] Donoho D L. De-noising by soft-thresholding[J]. IEEE Transactions on Information Theory, 1995, 41(3):613~627 [4] Guo H, Odegard J E, Lang M, %et al%. Wavelet based speckle reduction with application to SAR based ATD/R[J]. IEEE International Conference on Image Processing, 1994, 1:75~79 [5] Sveinsson J R, Hranfnkelsson A M, Benediktsson J A. Multiple wavelet transforms for speckle reduction of SAR images . International Geoscience and Remote Sensing Symposium (IGARSS) (Vol.2) . Piscataway:Institute of Electrical and Electronics Engineers Inc, 1999.1321~1324 [6] White R G. Cross-section estimation by simulated annealing . International Geoscience and Remote Sensing Symposium (IGARSS) (Vol.4) . Piscataway:IEEE,1994. 2188~2190 [7] Sveinsson J R, Benediktsson J A. Speckle reduction and enhancement of SAR images in the wavelet domain . International Geoscience and Remote Sensing Symposium (IGARSS) (Vol.1) . Piscataway:IEEE, 1996.63~66 [8] Zhang Jun, Cheng Xueguang, Liu Jian. Speckle reduction algorithm by soft-thresholding based on wavelet filters for SAR images . International Conference on Signal Processing Proceedings, ICSP(Vol.2) .Piscataway:IEEE,1998. 1469~1472 [9] 燕 英,周荫清. 模拟退火法在SAR单视图像中斑点噪声抑制中的应用研究[J]. 电子学报, 2003, 31(12):1903~1907 Yan Yin, Zhou Yinqing. Speckle removal for SAR single-look image by simulated annealing[J]. Acta Electronica Sinica, 2003, 31(12):1903~1907(in Chinese) [10] Daubechies I. Ten lectures on wavelets[M]. Philadelphia:SIAM, 1992 [11] Daubechies I. Orthonormal bases of compactly supported wavelets . http://www.qiji.cn/eprint/abs/1592.html, 2004-10-04 [12] Mallat S G. Theory for multiresolution signal decompositon:the wavelet representation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11(7):674~693 [13] Chapa J O, Rao R M. Algorithm for designing wavelets to match a specified signal[J]. IEEE Transactions on Signal Processing, 2000, 48(12):3395~3406 [14] Patuck N, McLernon D. Optimization of orthogonal wavelets for image compression . IEEE International Conference on Acoustics, Speech, and Signal Processing(Vol.3) . Piscataway:Institute of Electrical and Electronics Engineers Inc, 2004. 653~656
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出版历程
  • 收稿日期:  2005-06-17
  • 网络出版日期:  2006-03-31

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