摘要
图像边缘检测的关键是在尽量多检测到边缘的同时更有效地抑制噪声,为此提出了一种融合小波变换和形态学差分算法的边缘检测方法。将源图像进行小波分解,高频分量利用小波模极大值算法进行边缘检测,可有效提取高频边缘;低频分量采用形态学差分算法进行边缘检测,能够检测出低频边缘;采用一定的融合规则将两个边缘检测图像融合在一起。实验结果表明,该方法优于单独使用小波模极大值法或数学形态学法,对噪声具有很好的鲁棒性,得到的图像边缘连续、清晰。
The key to image edge detection is to suppress noises more effectively while detecting as much as possible the edges of image. For this purpose, this paper proposes an edge detection method based on the fusion of wavelet transform and morphology difference algorithm. The image is divided by wavelets, and then the algorithm of the wavelet modulus maxima is applied to the high frequency part of the image, so noises can be suppressed effectively. The morphology difference algorithm is applied to the low frequency part of the image, so weak edges can be detected with high quality. The two edge images are fused according to some fusion rules. The experimental results show that the approach is superior to wavelet modulus maxima algorithm or mathematical morphological method alone and is good robust to noise and the edge is consecutive and clear.
出处
《计算机工程与应用》
CSCD
2012年第35期174-177,181,共5页
Computer Engineering and Applications
基金
国家自然科学青年基金(No.41104096)
江苏师范大学自然科学基金(No.09XLA04)
关键词
小波变换
边缘检测
差分算法
图像融合
wavelet transform
edge detection
difference algorithm
image fusion
