Ultrasonic speckle denoising using the combination of wavelet transform and Wiener filter

S. Udomhunsakul, P. Wongsita
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引用次数: 10

Abstract

Ultrasonic images are inherently affected by multiplicative noise, which is due to the coherent wave interference in tissue. This paper presents a method for ultrasonic speckle denoising using the combination of wavelet transform and wiener filter to effectively reduce the speckle noise while preserving the resolvable details. In our method, the steps involved are finding the 2D discrete wavelet transform of the logarithmic image. Then, the wiener filter is used to apply over areas in each detail subband (HH,HL and LH). Next the inverse wavelet transform is computed and applying the inverse logarithm. To evaluate the denoising performance, mean square error (MSE), signal to mean square error (S/mse) and edge preservation (/spl beta/) are used. From the experimental results, we found that our approach leads to an effective method for ultrasonic speckle denoising.
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基于小波变换和维纳滤波的超声斑点去噪方法
超声图像固有地受到乘性噪声的影响,这是由于组织中的相干波干涉。提出了一种将小波变换与维纳滤波相结合的超声散斑去噪方法,在保留可分辨细节的同时有效地降低了散斑噪声。在我们的方法中,所涉及的步骤是找到对数图像的二维离散小波变换。然后,使用维纳滤波器对每个细节子带(HH,HL和LH)的区域进行应用。然后计算小波逆变换并应用逆对数。为了评估去噪性能,使用均方误差(MSE),信号对均方误差(S/ MSE)和边缘保持(/spl beta/)。实验结果表明,该方法是一种有效的超声散斑去噪方法。
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