光电工程, 2020, 47 (1): 190268, 网络出版: 2020-02-24   

多颜色空间的内窥镜图像血管增强方法

Vessel enhancement of endoscopic image based on multi-color space
作者单位
浙江大学光电科学与工程学院, 浙江杭州 310007
摘要
为了提高医用电子内窥镜所获图像的血管与组织的对比度, 针对内窥镜血管图像的特点, 提出了一种基于多颜色空间非线性对比度拉伸的血管增强处理方法。首先在 RGB颜色空间利用非线性映射函数对绿色(G)分量进行自适应对比度拉伸; 接着依据 G分量的拉伸结果, 相应地调整红色 (R)和蓝色(B)两个分量的灰度值; 然后将图像转换到 HSV颜色空间, 并对图像的饱和度(S)分量进行自适应对比度拉伸; 最后将图像转换回 RGB颜色空间, 最终达到血管增强的目的。在本文中, 利用所提出的算法对多幅电子内窥镜图像进行处理, 结果表明, 算法对于原始特征不明显的细小血管也具有较好的增强效果。通过与其它的增强方法相对比, 增强后图像的细节方差 (DV)显著大于其它方法。将算法嵌入到分辨率为 1280×800的内窥镜软件中, 其处理速度可达 26 f/s。
Abstract
In order to improve the contrast between the blood vessels and tissues of the images obtained by medical electronic endoscopes, a vessel enhancement method of non-linear contrast stretching in multi-color space is proposed according to the characteristics of endoscopic vascular images. Firstly, in RGB color space, stretching contrast adaptively of the green (G) component by using the nonlinear mapping function. Secondly, adjusting the gray value of the two components of red (R) and blue (B) according to the stretching result of the G component. Thirdly, converting the image to HSV color space, and stretching contrast adaptively of the saturation (S) component of the image. Finally, converting the image back to RGB color space, and the purpose of vessel enhancement is achieved. In this paper, the proposed algorithm is used to process several electronic endoscopic images with different contrast and brightness. The results show that the algorithm has better enhancement effect on small blood vessels which are not obvious in original features. Comparing to other enhancement methods, the detail variance (DV) of the enhanced image is significantly great. The algorithm is embedded in a resolution of 1280×800 endoscopic software, 26 frames can be processed per second.

王强, 陶沛, 袁波, 王立强. 多颜色空间的内窥镜图像血管增强方法[J]. 光电工程, 2020, 47(1): 190268. Wang Qiang, Tao Pei, Yuan Bo, Wang Liqiang. Vessel enhancement of endoscopic image based on multi-color space[J]. Opto-Electronic Engineering, 2020, 47(1): 190268.

本文已被 1 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!