基于MAP的超声图像分解去噪算法研究

doi:10.3969/j.issn.0372-2112.2014.07.008

电子学报 ›› 2014, Vol. 42 ›› Issue (7): 1291-1298.DOI: 10.3969/j.issn.0372-2112.2014.07.008

基于MAP的超声图像分解去噪算法研究

李春芳¹, 杨鑫², 张旭明¹, 丁明跃^1,3

1. 华中科技大学生命科学与技术学院, 生物医学工程系, 图像信息处理与智能实验室, 湖北武汉 430074;
2. 华中科技大学图像识别与人工智能研究所, 多谱信息处理技术国防科技重点实验室, 湖北武汉 430074;
3. 湖北科技学院生物医学工程学院, 湖北咸宁 437100

收稿日期:2013-08-19 修回日期:2013-10-22 出版日期:2014-07-25
- 通讯作者:
- 丁明跃
- 作者简介:
- 李春芳 女，1990年2月出生于重庆市云阳县.研究生.主要研究方向为医学图像处理.E-mail：cfli2012@126.com；杨鑫男，1984年11月出生于湖北省武汉市.博士.主要研究方向为医学图像处理.E-mail：loveashun@gmail.com
- 基金资助:
- 国家自然科学基金国际合作项目 (No.30911120497）; 国家科技支撑计划项目 (No.2012BA113B02）; 国家自然科学基金青年基金项目 (No.61001141）; 湖北公益性科技研究项目 (No.2012DCA06001）

MAP Based Ultrasound Image Decomposition and Denoising Method

LI Chun-fang¹, YANG Xin², ZHANG Xu-ming¹, DING Ming-yue^1,3

1. Image Processing and Intelligence Control Key Laboratory of Education Ministry of China, Department of Bio-medical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China;
2. State Key Laboratory for Multi-spectral Information Processing Technologies, Institute for Pattern Recognition and Artificial Intelligence (IPRAI), Huazhong University of Science and Technology, Wuhan, Hubei 430074, China;
3. School of Bio-medical Engineering, Hubei University of Science and Technology, Xianning, Hubei 437100, China

Received:2013-08-19 Revised:2013-10-22 Online:2014-07-25 Published:2014-07-25
- Supported by:
- Projects of International Cooperation and Exchanges of National Natural Science Foundation of China (No.30911120497); Project of National Key Technology R&D Program (No.2012BA113B02); Youth Fund of National Natural Science Foundation of China (No.61001141); Special Research Fund for Non-profit Sector of Hubei Province (No.2012DCA06001)

摘要/Abstract

摘要：

超声图像中的斑点噪声，降低图像分辨率和对比度，不利于后续图像处理.本文基于最大后验概率（Maximum A Posteriori，MAP）推导出一种新的超声图像分解算法，将原始超声图像分解为无散斑真实图像和散斑图像.使用六组不同的参数值，对Field II仿真的超声图像进行分解试验，得出算法中比例参数对分解结果的影响规律.用该方法分解三幅人体超声图像，得到的真实图像平滑性好，且能较好的保留细节和边缘.本文提出的分解算法可用于超声图像的去噪，且分解得到的真实图像和散斑图像可用于特征提取、图像分割和图像分类等.

关键词: 超声图像分解, 最大后验概率估计, 斑点噪声, 全变差去噪

Abstract:

The speckle noise in ultrasound images reduces image resolution and contrast,and brings difficulty to subsequent image processing.Based on MAP (Maximum A Posteriori),the paper proposes an ultrasound image decomposition method,to decompose an observed image into a speckle-free true image and a speckle image.We use Field II to simulate an ultrasound image,and decompose it with the proposed method.By six tests with different parameters,we study how the weighted parameters influence the decomposition results.Then we use this method to decompose three real ultrasound images.The true image we get by decomposition can be seen as the denoised image,because it has good homogeneity,and preserves details and edges well.Both the true image and the speckle can be used in feature extraction,image segmentation,classification and so on.

Key words: image decomposition, maximum a posterior estimation, speckle noise, total variation denoising

中图分类号:

TP391.41

李春芳, 杨鑫, 张旭明, 等. 基于MAP的超声图像分解去噪算法研究[J]. 电子学报, 2014, 42(7): 1291-1298.

LI Chun-fang, YANG Xin, ZHANG Xu-ming, et al. MAP Based Ultrasound Image Decomposition and Denoising Method[J]. Acta Electronica Sinica, 2014, 42(7): 1291-1298.

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基于MAP的超声图像分解去噪算法研究

MAP Based Ultrasound Image Decomposition and Denoising Method

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