基于bmd的逐像素维纳滤波超声图像散斑去除技术

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Bhawna Gupta, V. Khandelwal
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引用次数: 0

摘要

本文提出了一种改进的基于二维经验模态分解(BEMD)的超声图像散斑去除技术。将噪声图像分解为其固有模态函数(IMFs)和残差。通过逐像素维纳滤波去除低阶imf的噪声分量。利用滤波后的低阶imf、高阶imf和残差对图像进行重构。在具有不同方差噪声分量的合成超声图像和真实超声图像上测试了该方法的性能。实验结果表明,该算法在各种图像质量矩阵方面都优于现有的合成图像和真实超声图像方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BEMD Based Ultrasound Image Speckle Reduction Technique Using Pixel-Wise Wiener Filtering
In this paper, an improved Bidimensional Empirical Mode Decomposition (BEMD) based speckle reduction technique for ultrasound images has been proposed. The noisy image has been decomposed into its Intrinsic Mode Functions (IMFs) and a~residue. The noise component of the low order IMFs is removed with the pixel-wise Wiener filtering. The image is reconstructed with these filtered low order IMFs, high order IMFs and the residue. The performance of the proposed method has been tested on synthetic as well as real ultrasound images having noise components of different variance. The experimental results show that the proposed algorithm performs better than other existing methods for synthetic images as well as real ultrasound images in terms of various image quality matrices.
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来源期刊
Advances in Electrical and Electronic Engineering
Advances in Electrical and Electronic Engineering ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
1.30
自引率
33.30%
发文量
30
审稿时长
25 weeks
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