Ultrasonic speckle reduction based on soft thresholding in quaternion wavelet domain

Jing Jin, Yipeng Liu, Qiang Wang, Shen Yi
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引用次数: 13

Abstract

Speckle reduction is a tough task for ultrasound images processing resulting to their low resolution and contrast. Quaternion wavelet (QW) is of some superior properties compared to discrete wavelets, such as nearly shift-invariant wavelet coefficients and phase based texture presentation. So we aim to exploit the excellent performances of speckle reduction in quaternion wavelet domain (QWD) based on the soft thresholding method. The algorithm uses quaternion wavelet transform (QWT) to decompose the ultrasound images, and then apply five typical criterions to set threshold for QW coefficients. Furthermore, we conduct two experiments on a synthetic speckle image and a real ultrasound image. The performance of the proposed speckle reduction algorithm, using QWT with soft thresholding, is demonstrated superior to that using wavelet transform (WT) and classical algorithms.
基于四元数小波域软阈值的超声散斑抑制
由于超声图像的低分辨率和低对比度,斑点去除一直是超声图像处理的难点。与离散小波相比,四元数小波具有近似位移不变的小波系数和基于相位的纹理表示等优点。因此,我们的目标是利用基于软阈值法的四元数小波域(QWD)散斑抑制的优良性能。该算法采用四元数小波变换(QWT)对超声图像进行分解,然后应用5种典型准则对QW系数设置阈值。在此基础上,我们分别对合成的散斑图像和真实的超声图像进行了实验。结果表明,采用带有软阈值的量子小波变换的散斑消减算法的性能优于采用小波变换和经典算法的散斑消减算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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