摘要
提出了一种基于小波提升和形态学的图像边缘检测方法。对源图像进行小波分解,用数学形态学法对低频子图像进行边缘检测,用小波变换法对不同分解层上的高频子图像进行边缘检测,采用一定的融合规则将这两个边缘图像融合在一起得到一幅完好的边缘图像。这种边缘检测方法结合了小波提升法和数学形态学法的优点,对用这两种方法得到的边缘信息进行融合,有效地抑制了噪声,且边缘连续、清晰。实验结果表明,提出的这种结合方法优于单独使用数学形态学法或小波提升法。
An edge detection Algorithm based on lifting wavelet and morphology was proposed. First, the source image was decomposed by wavelet lifting, using mathematical morphological method extracts edges in low-frequency approximate image and using wavelet transform method extracts edges in high-frequency detailed images on the different levels, then the two edge images were fused according to some fusion rules to obtain an integrated and clear edge image. This edge detection method combines the advantages of wavelet lifting method and mathematical morphological method, which fuses the two edge information obtained by different methods, so the noises are restrained effectively and the edges are consecutive and clear. The experimental results show that the approach is superior to mathematical morphological method and wavelet transform method alone.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2006年第z2期869-871,共3页
Journal of System Simulation
关键词
边缘检测
融合技术
小波提升
数学形态学
image processing
edge detection
fusion technique
fusion rule
Canny operator
wavelet transform
