华南理工大学学报(自然科学版) ›› 2009, Vol. 37 ›› Issue (1): 48-53.

• 电子、通信与自动控制 • 上一篇    下一篇

血管内超声图像的血液噪声抑制和对比度增强算法

李虹王惠南董海艳章哓国3   

  1. 1. 南京航空航天大学 自动化学院, 江苏 南京 210016; 2. 南京中医药大学 信息技术学院, 江苏 南京 210046; 3. 东南大学 附属中大医院 心脏介入中心, 江苏 南京 210009
  • 收稿日期:2007-11-27 修回日期:2008-01-17 出版日期:2009-01-25 发布日期:2009-01-25
  • 通信作者: 李虹(1975-),女,博士,主要从事医学图像处理及分析研究. E-mail:lihonglilan@yahoo.com.cn
  • 作者简介:李虹(1975-),女,博士,主要从事医学图像处理及分析研究.
  • 基金资助:

    国家自然科学基金资助项目(60502030)

Algorithm of Noise Reduction and Contrast Enhancement for Intravascular Ultrasound Images

Li Hong1  Wang Hui-nan1  Dong Hai-yan2  Zhang Xiao-guo3   

  1. 1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu, China; 2. Information Technic College, Nanjing University of Traditional Chinese Medicine, Nanjing 210046, Jiangsu, China; 3. Center of Heart Intervention of Zhongda Hospital, Southeast University, Nanjing 210009, Jiangsu, China
  • Received:2007-11-27 Revised:2008-01-17 Online:2009-01-25 Published:2009-01-25
  • Contact: 李虹(1975-),女,博士,主要从事医学图像处理及分析研究. E-mail:lihonglilan@yahoo.com.cn
  • About author:李虹(1975-),女,博士,主要从事医学图像处理及分析研究.
  • Supported by:

    国家自然科学基金资助项目(60502030)

摘要: 针对血管内超声图像中的血液斑点噪声和边缘模糊等问题,提出基于二进小波变换的噪声抑制和对比度增强算法.根据血管内超声成像的特点估计噪声的方差,由二进小波变换的分解结构给出局部阈值的计算方法,并结合软阈值滤波法和硬阈值滤波法对不同尺度的小波系数进行萎缩处理,同时利用小波系数极值拉伸和Hermite多项式插值增强图像的对比度.实验结果表明,与现有血管内超声图像去噪方法相比,文中方法在抑制血液斑点噪声的同时增强了图像对比度,保留了图像的细节,具有更好的实用性.

关键词: 图像处理, 血液斑点噪声抑制, 对比度增强, 小波变换

Abstract:

In order to overcome the blood-speckle noise and ambiguous boundary in intravascular ultrasound (IVUS) images, this paper proposes an algorithm for noise reduction and contrast enhancement based on the dyadic wavelet transform. In this algorithm, first, the noise variance is estimated according to the characteristics of IVUS images. Next, a method to calculate the local threshold is proposed based on the decomposed structure of dyadic wavelet transform. Then, the wavelet coefficients in different scales are treated using the shrinkage techniques which combine the soft threshold filtering with the hard one. Finally, a contrast enhancement algorithm is proposed based on the stretching of wavelet coefficient extreme and on the interpolating with Hermite polynomials. Experimental results indicate that, as compared with the existing denoising methods, the proposed algorithm is more practicable because it not only reduces the blood speckle noise but also enhances the image contrast without eliminating image details.

Key words: image processing, blood-speckle noise reduction, contrast enhancement, wavelet transform