Journal of Computer Applications ›› 2012, Vol. 32 ›› Issue (11): 3218-3220.DOI: 10.3724/SP.J.1087.2012.03218

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Improved anisotropic diffusion ultrasound image denoising method based on logarithmic compression

YANG Jin,LIU Zhi-qin,WANG Yao-bin,GAO Xiao-ming   

  1. School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang Sichuan 621010,China
  • Received:2012-05-28 Revised:2012-07-17 Online:2012-11-12 Published:2012-11-01
  • Contact: YANG Jin
  • Supported by:
    Scientific Research Fund of SiChuan Provincial Science & Technology Department

基于对数压缩的超声各向异性扩散去噪方法

杨金,刘志勤,王耀彬,高小明   

  1. 西南科技大学 计算机科学与技术学院,四川 绵阳 621010
  • 通讯作者: 杨金
  • 作者简介:杨金(1988-),男,四川绵阳人,硕士研究生,CCF会员,主要研究方向:医学图像处理;刘志勤(1962-),女,四川绵阳人,教授,主要研究方向:高性能计算;王耀彬(1982-),男,四川乐山人,讲师,博士,主要研究方向:医学图像处理;高小明(1980-),男,四川广安人,讲师,硕士,主要研究方向:医学图像处理、嵌入式系统。
  • 基金资助:
    四川省科技厅项目(11ZS2011,2010GZ0134)

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.

Key words: anisotropic diffusion, logarithmic compression, diffusion coefficient, ultrasound image, speckle noise

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

CLC Number: