Speckle reducing anisotropic diffusion
Speckle reducing anisotropic diffusion
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DOI：
10.1109/tip.2002.804276
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发表时间：
2002-11-01
影响因子：
10.6
通讯作者：
Acton, ST
中科院分区：
文献类型：
--
作者：
Yu, YJ;Acton, ST
本文提供了散斑减少各向异性扩散（SRAD），扩散方法定制的超声和雷达成像应用程序的推导。SRAD是用于斑点图像的边缘敏感扩散，以与常规各向异性扩散是用于被加性噪声破坏的图像的边缘敏感扩散相同的方式。我们首先表明，李和弗罗斯特过滤器可以被铸造为偏微分方程，然后我们推导出SRAD允许边缘敏感的各向异性扩散在这方面。正如Lee和Frost滤波器在自适应滤波中利用变异系数一样，SRAD利用瞬时变异系数，该瞬时变异系数被示出为局部梯度幅度和拉普拉斯算子的函数。我们使用合成和真实的线性扫描超声图像的颈动脉验证新算法。我们还证明了算法的性能与真实的SAR数据。通过计算机模拟的颈动脉图像的性能指标进行了比较，与现有的三个斑点减少计划。在存在斑点噪声的情况下，斑点减少各向异性扩散优于传统的斑点去除滤波器和传统的各向异性扩散方法的均值保持，方差减少，和边缘定位。
This paper provides the derivation of speckle reducing anisotropic diffusion (SRAD), a diffusion method tailored to ultrasonic and radar imaging applications. SRAD is the edge-sensitive diffusion for speckled images, in the same way that conventional anisotropic diffusion is the edge-sensitive diffusion for images corrupted with additive noise. We first show that the Lee and Frost filters can be cast as partial differential equations, and then we derive SRAD by allowing edge-sensitive anisotropic diffusion within this context. Just as the Lee and Frost filters utilize the coefficient of variation in adaptive filtering, SRAD exploits the instantaneous coefficient of variation, which is shown to be a function of the local gradient magnitude and Laplacian operators. We validate the new algorithm using both synthetic and real linear scan ultrasonic imagery of the carotid artery. We also demonstrate the algorithm performance with real SAR data. The performance measures obtained by means of computer simulation of carotid artery images are compared with three existing speckle reduction schemes. In the presence of speckle noise, speckle reducing anisotropic diffusion excels over the traditional speckle removal filters and over the conventional anisotropic diffusion method in terms of mean preservation, variance reduction, and edge localization.