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用于超声斑点噪声滤波的各向异性扩散新模型

DOI: 10.3724/SP.J.1004.2012.00412, PP. 412-419

Keywords: 各向异性平滑,斑点滤波,超声图像,局部统计

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Abstract:

?由于扩散系数的缺点,原斑点噪声各向异性扩散模型(Specklereducinganisotropicdiffusion,SRAD)有产生板块效应、模糊弱边界与细节等缺点.本文通过改进扩散系数,提出一种新的斑点噪声各项异性扩散模型(Newspecklereducinganisotropicdiffuse,NSRAD),NSRAD中采用一个S型函数作为扩散系数:在同质区域中,采用各向同性扩散,避免了板块效应;在结构性区域中,扩散速度变化敏感,同时以更快趋向于0的速度扩散,因此,提高了该区域的分辨率,达到增强细节和弱边界以及保留边界的锐利性的目的.仿真图像的定量分析证明新方法不仅比原SRAD除噪更有效,而且提高了除噪后图像与原图像的结构相似性,同时具有更小形变.真实图像的试验结果也证明新方法在有效除噪的同时消除了黑板刷效应,增强了边界以及细节.

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