,two dimensional variational mode decomposition ( 2D-VMD), bhattacharyya distance ( BD), intrinsic mode functions, medical image denoising ,"/> 基于<span> 2D-VMD </span>和<span> BD </span>结合的医学图像去噪算法

吉林大学学报(信息科学版) ›› 2024, Vol. 42 ›› Issue (1): 186-192.

• • 上一篇    

基于 2D-VMD BD 结合的医学图像去噪算法

马元元1 , 崔长彩2 , 马立园2 , 东 辉3   

  1. 1. 北京诺华制药有限公司 全球药物研发部, 北京 100000; 2. 华侨大学 制造工程研究院, 福建 厦门 361021; 3. 福州大学 机械工程及自动化学院, 福州 350116
  • 收稿日期:2023-01-19 出版日期:2024-01-29 发布日期:2024-02-04
  • 通讯作者: 崔长彩(1972— ), 女, 山东青岛人, 华侨大学教授, 博士生导师, 主要从事半导体薄膜光电特性和几何特性的测量与表征、 图像分析与处理、 智能优化算法与应用等研究, ( Tel) 86- 18695682866(E-mail)cuichc@ hqu. edu. cn
  • 作者简介:马元元(1989— ), 女, 天津人, 北京诺华制药有限公司药品注册专员, 主要从事药品研发、 注册和上市研究, (Tel)86- 15022373397(E-mail)2546093947@ qq. com

Medical Image Denoising Algorithm Based on 2D-VMD and BD

MA Yuanyuan 1 , CUI Changcai 2 , MA Liyuan 2 , DONG Hui 3   

  1. 1. Global Drug Development Department, Beijing Novartis Pharmaceutical Company Limited, Beijing 100000, China; 2. Institute of Manufacturing Engineering, Huaqiao University, Xiamen 361021, China; 3. School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350116, China
  • Received:2023-01-19 Online:2024-01-29 Published:2024-02-04

摘要:  为提高去噪图像质量, 提出了一种基于二维变分模态分解算法(2D-VMD: Two Dimensional Variational Mode Decomposition)和巴氏距离( BD: Bhattacharyya Distance) 的结合算法用于图像去噪。 该算法首先使用 2D-VMD算法将图像分解为若干个固有模态函数( IMFs: Intrinsic Mode Functions); 然后使用 BD 测量每个 IMF 的概率密度函数(PDF: Probability Density Function)与原图像 PDF 间的几何距离, 区分出信号主导 IMF 和噪声 主导 IMF; 最后将噪声主导 IMF 经小波阈值去噪后与信号主导 IMF 重构, 得到去噪图像。 将算法应用于医学 图像去噪, 理论分析和仿真结果表明, 2D-VMD BD 结合算法与全变分模型(ROF: Rudin Osher Fatemi)算法、 中值滤波和小波阈值滤波相比, 其在主观和客观评价方面都具有较好的去噪效果, 有效地提高了去噪图 像质量。 

关键词: 二维变分模态分解, 巴氏距离, 概率密度函数, 医学图像去噪

Abstract:  In order to improve the quality of denoised images, an algorithm based on 2D-VMD ( Two Dimensional Variational Mode Decomposition ) and BD ( Bhattacharyya Distance ) is proposed for image denoising. Firstly, the algorithm uses 2D-VMD algorithm to decompose the image into several IMFs ( Intrinsic Mode Functions), and then BD is used to measure the geometric distance between the PDF (Probability Density Function) of each IMF and the original image to distinguish the signal-dominated IMF and the noise-dominated IMF. Finally, the denoising noise-dominated IMF through wavelet threshold denoising and the signal-dominated IMF are reconstructed to obtain the denoised image. The proposed algorithm is applied to medical images. The theoretical analysis and simulation result show that, compared with ROF ( Rudin Osher Fatemi) algorithm, median filter and wavelet threshold algorithm, the algorithm of combining 2D-VMD and BD has better denoising effect in both subjective and objective evaluation, and it effectively improves the quality of denoised images. 

Key words:  ')">

 , two dimensional variational mode decomposition ( 2D-VMD), bhattacharyya distance ( BD), intrinsic mode functions, medical image denoising