摘要
医学图像在现代医疗诊断中起着不可低估的重要诊断作用。本文根据甲襞微循环图像的特点,采用三次B样条小波对甲襞显微图像进行小波变换,利用模局部极大值方法较好地检测出图像的边缘,定位精度较高。克服了传统的梯度法、灰度法和改进型自适应阈值模板相关匹配算法的不足。
Medical image edge detection is significant to clinical diagnosis. This paper discusses the principle of the wavelet transformation and local maximum module algorithm. According to the peculiarity of the nail fold micro-circulation image, using 3-Spline binary wavelet, we detect the edges of it. Compared with classical methods of edge detection, it provides higher precision and saves more details.
出处
《微计算机信息》
北大核心
2007年第03X期305-306,302,共3页
Control & Automation
基金
本课题受到以下项目资助(NSFC(NO.60572051)
05FZ25
05FZ04)
关键词
样条
小波变换
极大模
甲襞微循环图像
spline, wavelet Analysis, maximum module, nail fold micro-circulation images
