摘要
针对传统Canny算子抑制噪声和检测低强度边缘能力不足的问题,提出一种将LOG算子和Canny算子相结合的边缘检测方法。采用LOG算子对图像进行噪声过滤,从以下3个方面改进Canny算子实现边缘检测:(1)设计高斯滤波核对过滤掉噪声的图像进行边缘增强,使低强度边缘更容易被检测;(2)在M×N邻域中计算梯度幅值和方向;(3)将梯度方向结合梯度幅值计算,使梯度幅值在边缘检测中更具依据性。对增加椒盐噪声的图像进行实验,结果表明,该方法在最大程度抑制噪声的同时,能检测到更多的低强度边缘。
Aiming at the disability of traditional Canny operator in noise suppression and detecting low-intensity edge, this paper proposes an edge detection method combined LOG operator and Canny operator. LOG operator is used to the picture for noise filtering and Canny operator is improved in the flowing three aspects to execute the edge detection： （1）It designs Gaussian smoothing kernel to intense the edge of picture filtered noise, which makes the low-intensity edge detect easily; （2）Gradient magnitude and direction are calculated by pixels within a M-by-N neighborhood; （3）It integrates gradient direction with the calculation of gradient magnitude, which can be the ground for gradient magnitude in edge detection. Through carrying out a lot experiment for picture increased salt and pepper noise, the method proposed in this paper can not only suppress noise in the largest degree, but also detect more low-intensity edge.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第3期210-212,共3页
Computer Engineering
基金
国家科技型中小企业技术创新基金资助项目(09C26213203797)
关键词
CANNY算子
LOG算子
高斯滤波核
梯度核
梯度幅值
Canny operator
LOG operator
Gaussian smoothing kernel
gradient kernel
gradient magnitude
作者简介
贺强（1984-），男，硕士研究生，主研方向：模式识别，图像处理； E—mail：heqiangcug@163．com
晏立，教授
