Ultrasound image anisotropic diffusion de-speckling method based on Mallat-Zhong discrete wavelet transform wavelet

Wu Shibin, Chen Bo, D. Wangli, G. Xiaoming
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Abstract

In view of speckle noise in ultrasound image, there are some disadvantages of traditional anisotropic diffusion methods, such as in-sufficient noise suppression and edge details preservation. A de-speckling method based on Mallat-Zhong Discrete Wavelet Transform( MZ-DWT) wavelet was proposed. The method used MZ-DWT wavelet and Expectation Maximization( EM) algorithm as the discrimination factor between homogeneous and edge regions, making it more accurately to control diffusion intensity and rate and achieving the noise suppression and details preservation. The experimental results show that, the proposed algorithm can better de-speckle while preserving image details and the performance of the method is better than the traditional anisotropic diffusion methods.
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基于Mallat-Zhong离散小波变换的超声图像各向异性扩散去斑方法
针对超声图像中存在的散斑噪声,传统的各向异性扩散方法存在噪声抑制不足、边缘细节保存不足等缺点。提出了一种基于Mallat-Zhong离散小波变换(MZ-DWT)小波的去斑方法。该方法采用MZ-DWT小波和期望最大化(EM)算法作为均匀区域和边缘区域的区分因子,更准确地控制扩散强度和扩散速率,实现了噪声抑制和细节保留。实验结果表明,该算法在保留图像细节的同时能较好地去斑,其性能优于传统的各向异性扩散方法。
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