{"title":"Speckle suppression by adaptive nonlinear filtering","authors":"S. Ghofrani, A. Ayatollahi","doi":"10.1109/VIPROM.2002.1026648","DOIUrl":null,"url":null,"abstract":"Using a good statistical model of speckle formation is important in designing an adaptive filter for speckle reduction in ultrasound B-scan images. Most clinical ultrasound imaging systems use a nonlinear logarithmic function to reduce the dynamic range of the input echo signal and emphasize objects with weak backscatter. The statistic of log-compressed images for Nakagami distribution was derived (Ghofrani et al. 2001) and in this paper we use the results for designing an adaptive nonlinear filter in speckle reduction. We processed two original ultrasound images of kidney and liver to demonstrate the efficiency of the designed filter.","PeriodicalId":223771,"journal":{"name":"International Symposium on VIPromCom Video/Image Processing and Multimedia Communications","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on VIPromCom Video/Image Processing and Multimedia Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VIPROM.2002.1026648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Using a good statistical model of speckle formation is important in designing an adaptive filter for speckle reduction in ultrasound B-scan images. Most clinical ultrasound imaging systems use a nonlinear logarithmic function to reduce the dynamic range of the input echo signal and emphasize objects with weak backscatter. The statistic of log-compressed images for Nakagami distribution was derived (Ghofrani et al. 2001) and in this paper we use the results for designing an adaptive nonlinear filter in speckle reduction. We processed two original ultrasound images of kidney and liver to demonstrate the efficiency of the designed filter.
利用良好的散斑形成统计模型对设计一种自适应滤波器来降低b超扫描图像中的散斑是非常重要的。大多数临床超声成像系统使用非线性对数函数来减小输入回波信号的动态范围,并强调弱反向散射的物体。导出了Nakagami分布的对数压缩图像的统计量(Ghofrani et al. 2001),并在本文中使用该结果设计了一种自适应非线性散斑减少滤波器。我们对肾脏和肝脏的两张原始超声图像进行了处理,以证明所设计的滤波器的效率。