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基于对数压缩的超声各向异性扩散去噪方法
引用本文:杨金,刘志勤,王耀彬,高小明.基于对数压缩的超声各向异性扩散去噪方法[J].计算机应用,2012,32(11):3218-3220.
作者姓名:杨金  刘志勤  王耀彬  高小明
作者单位:西南科技大学 计算机科学与技术学院,四川 绵阳 621010
基金项目:四川省科技厅项目(11ZS2011,2010GZ0134)
摘    要:针对当前超声图像去噪算法很难同时做到降噪和边缘保持的情况,在进行各向异性扩散模型研究的基础上,提出基于对数压缩的改进各向异性扩散算法(LCAD)去除超声散斑噪声。算法将图像对数压缩后进行噪声分布模型估计,然后构造基于广义伽马分布的扩散系数,在扩散过程中达到降噪和边缘保持效果。

关 键 词:各向异性扩散    对数压缩    扩散系数    超声图像    散斑噪声
收稿时间:2012-05-28
修稿时间:2012-07-17

Improved anisotropic diffusion ultrasound image denoising method based on logarithmic compression
YANG Jin,LIU Zhi-qin,WANG Yao-bin,GAO Xiao-ming.Improved anisotropic diffusion ultrasound image denoising method based on logarithmic compression[J].journal of Computer Applications,2012,32(11):3218-3220.
Authors:YANG Jin  LIU Zhi-qin  WANG Yao-bin  GAO Xiao-ming
Affiliation:School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang Sichuan 621010,China
Abstract:Current ultrasound image denoising algorithms cannot maintain edge well while denoising. An improved anisotropic diffusion denoising method called anisotropic diffusion based on Logarithmic Compression (LCAD) was proposed to reduce ultrasound speckle noise after the study of anisotropic diffusion model. The proposed method estimated noise distribution model after logarithmic compression of the image and then generated a diffusion coefficient based on generalized Gamma distribution to achieve denoising purpose while diffusing.
Keywords:anisotropic diffusion                                                                                                                          logarithmic compression                                                                                                                          diffusion coefficient                                                                                                                          ultrasound image                                                                                                                          speckle noise
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