融合双树复小波和改进形态学的视网膜图像增强

张丽娟; 殷婷婷; 李阳; 王珺楠; 刘颖

doi:10.3788/OPE.20172513.0235

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融合双树复小波和改进形态学的视网膜图像增强

信息科学 | 更新时间：2020-08-13

- 融合双树复小波和改进形态学的视网膜图像增强
- Intensification of retinal image integrating dual-tree complex wavelet and improved morphology
- 光学精密工程 2017年25卷第10s期页码：235-243
- 作者机构：
  
  1. 长春工业大学计算机科学与工程学院,吉林长春,130012
  2. 吉林财经大学管理科学与信息工程学院,吉林长春,130117
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目（No.61402193）();吉林省科技厅基金资助项目（No.20160418080FG）();吉林省教育厅基金资助项目（No.2014142
- DOI：10.3788/OPE.20172513.0235
  中图分类号： TP394.1
- 收稿日期：2017-06-05，
  
  修回日期：2017-07-10，
  
  纸质出版日期：2017-11-25
- 稿件说明：
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张丽娟, 殷婷婷, 李阳等. 融合双树复小波和改进形态学的视网膜图像增强[J]. 光学精密工程, 2017,25(10s): 235-243

ZHANG Li-juan, YIN Ting-ting, LI Yang etc. Intensification of retinal image integrating dual-tree complex wavelet and improved morphology[J]. Editorial Office of Optics and Precision Engineering, 2017,25(10s): 235-243
张丽娟, 殷婷婷, 李阳等. 融合双树复小波和改进形态学的视网膜图像增强[J]. 光学精密工程, 2017,25(10s): 235-243 DOI： 10.3788/OPE.20172513.0235.

ZHANG Li-juan, YIN Ting-ting, LI Yang etc. Intensification of retinal image integrating dual-tree complex wavelet and improved morphology[J]. Editorial Office of Optics and Precision Engineering, 2017,25(10s): 235-243 DOI： 10.3788/OPE.20172513.0235.

摘要

视网膜图像的增强受色差、对比度，血管密集等影响，增强难度高。为此提出一种结合双树复小波和形态学变换优点的增强方法。首先用双树复小波变换去分解视网膜图像；接着，把自适应阈值去噪应用在高频部分，针对低频部分，采用改进的形态学top-hat变换进行处理；最后，采用双树复小波的逆变化进行高低频部分重构，得到增强后的视网膜图像。为验证此算法，把DRIVE数据库中的40幅视网膜图像作为样本进行仿真实验。数据显示，本文算法可以使标准差，均值，信息熵等评价指标提高15%以上；在图像清晰度，差异度与失真度上，与其他算法相比，本文效果优化至少5%以上。综合来讲，本文算法在提高图像的整体视觉效果上具有良好的表现。

Abstract

In order to solve the problem that the intensification of retinal image affected by chromatic aberration

contrast and dense blood vessels etc

was hard to achieve

an intensification method of combing dual free complex wavelet (DT-CWT) and advantages of morphology transform was proposed. The retinal image was decomposed by using the transformation of dual-tree complex wavelet (DT-CWT)at first

and then adaptive wavelet threshold de-noising was applied to the high-frequency part and for the low-frequency part

top-hat transformation of improved morphology was adopted for its processing

finally

the high-frequency and low-frequency part were reconstructed by adopting the inverse transformation of dual free complex wavelet and the intensified retinal image was obtained. In order to verify the algorithm

40 retinal images in the DRIVE database were used as samples for simulation experiment. The data shows that standard deviation

mean value

information entropy and other evaluation indexes can be increased by more than 15% by using the algorithm of the thesis; for the image definition

diversity factor and degree of distortion are at least optimized by more than 5% compared with other algorithms. Arrivalling at a conclusion that the algorithm proposedperforms better in improving the overall visual effect of image.

关键词

Keywords

references

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