Despeckling of medical ultrasound images using Daubechies complex wavelet transform
Despeckling of medical ultrasound images using Daubechies complex wavelet transform
复制标题
DOI：
10.1016/j.sigpro.2009.07.008
复制
发表时间：
2010-02-01
影响因子：
4.4
通讯作者：
Jeon, Moongu
中科院分区：
文献类型：
--
作者：
Khare, Ashish;Khare, Manish;Jeon, Moongu
本文提出了一种基于Daubechies复数小波变换的去斑方法，针对医学超声图像，采用Daubechies复数小波变换，因为它具有近似平移不变性，并且与实小波域相比，复数小波域在虚平面上具有额外的信息。导出了小波收缩因子来估计无噪声小波系数。该方法首先使用复尺度系数的虚部检测强边缘，然后对小波域中非边缘点的复小波系数的幅度进行收缩。所提出的收缩取决于噪声图像的复小波系数的统计参数，这使得它本质上是自适应的。根据信号均方误差（SMSE）和信噪比（SNR）比较所提出方法的有效性。实验结果表明，该方法在测试图像上优于其他传统的去斑方法以及基于小波的对数变换和非对数变换方法。所提出的方法在真实诊断超声图像上的应用显示出比其他方法明显的改进。 (C) 2009 Elsevier B.V. 保留所有权利。
The paper presents a novel despeckling method, based on Daubechies complex wavelet transform, for medical ultrasound images, Daubechies complex wavelet transform is used due to its approximate shift invariance property and extra information in imaginary plane of complex wavelet domain when compared to real wavelet domain. A wavelet shrinkage factor has been derived to estimate the noise-free wavelet coefficients. The proposed method firstly detects strong edges using imaginary component of complex scaling coefficients and then applies shrinkage on magnitude of complex wavelet coefficients in the wavelet domain at non-edge points. The proposed shrinkage depends on the statistical parameters of complex wavelet coefficients of noisy image which makes it adaptive in nature. Effectiveness of the proposed method is compared on the basis of signal to mean square error (SMSE) and signal to noise ratio (SNR). The experimental results demonstrate that the proposed method outperforms other conventional despeckling methods as well as wavelet based log transformed and non-log transformed methods on test images. Application of the proposed method on real diagnostic ultrasound images has shown a clear improvement over other methods. (C) 2009 Elsevier B.V. All rights reserved.