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基于自适应微调因子的改进frost滤波 被引量:4

Modified frost filtering based on adaptive parameter
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摘要 为避免frost滤波因使用同一微调因子带来边缘细节等结构信息的模糊,以及等距等权所带来的盲目平滑现象,对frost滤波算法提出了一种改进方案。该方案综合考虑滤波窗口本身的局域统计特性以及窗口内各像素本身的统计特性来自适应确定微调因子。通过对真实合成孔径雷达图像进行改进算法降噪实验,以等效视数和边缘保持指数两项指标为评价标准,并与不同微调因子的Frost滤波输出结果进行比较,结果表明改进算法比原算法有很大的改进,在边缘保持和去噪方面具有更好的滤波性能。 To avoid the blurring of edges features by using the same parameter and blindfold caused by the same distance and weight in the sliding window when using frost filtering, a modified method of the frost filtering is proposed. This method mainly combines the statistical information of the filtering window and the statistical information of the each pixel of the window to adaptively compute the filter parameter. Then experiment is done to validate this method, the equivalent index and edge preservation index are used to evaluate the smoothing and edge preservation capability. While compared with the frost filtering ofthe different filtering parameters, this modified method has a better performance in terms of speckle noise suppressing and fine details preserving.
出处 《计算机工程与设计》 CSCD 北大核心 2011年第11期3793-3795,3843,共4页 Computer Engineering and Design
关键词 合成孔径雷达图像 相干斑噪声 局域统计 Frost滤波 自适应微调因子 t统计 synthetic aperture radar image speckle noise local statistics frost filtering adaptive parameter t statistic
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  • 1宁凯,李爱农,陈强,靳华安.基于小波NEIGHSHRINK阈值法滤除SAR斑点噪声[J].遥感信息,2014,29(2):7-14. 被引量:1
  • 2付洁,曹敏洁,汤谷云,罗涟玲,王修信.小波变换和模糊聚类的SAR图像斑点噪声去除[J].广西物理,2013,34(3):24-26. 被引量:2
  • 3王达心,王金刚.图像采集系统[J].电子测量技术,2005,28(5):56-57. 被引量:3
  • 4Bazi Y, Melgani F, Bruzzone L, et al. A genetic expectation maximization method for unsupervised change detection in multi- temporal SAR imagery [J]. International Journal of Remote Sensing, 2009, 30 (24): 6591-6610. 被引量:1
  • 5Bazi Y, Melgani F, Alsharari H. Unsupervised change detec- tion in multispectral remotely sensed imagery with level set methods [J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48 (8): 3178-3187. 被引量:1
  • 6Badri Narayan Subudhi, Francesca Bovolo, Ashish Ghosh, et al. Spatio-contextual fuzzy clustering with Markov random field model for change detection in remotely sensed images [J]. Op- tics & Laser Technology, 2014, 57: 284-292. 被引量:1
  • 7Su Linzhi, Gong Maoguo, Sun Bo, et al. Unsupervised change detection in SAR images based on locally fitting model and semi-EM algorithm [J]. International Journal of Remote Sensing, 2014, 35 (2): 621-650. 被引量:1
  • 8Ashish Ghosh, Niladri Shekhar Mishra, Susmita Ghosh. Fuzzy clustering algorithms for unsupervised change detection, in remote sensing images [J]. Information Sciences, 2011, 181 (4): 699-715. 被引量:1
  • 9Aghababaee H, Amini J, Tzeng YC. Improving change detec- tion methods of SAR images using fractals [J] Scientia Iranica, 2013, 20 (1): 15-22. 被引量:1
  • 10Haikel Hichri, Yakoub Bazi, Nail Alajlan, et al. Interactive segmentation for change detection in multispectral remote-sen- sing images [J]. IEEE Geoscience and Remote Sensing Let- ters, 2013, 10 (2): 298-302. 被引量:1

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