摘要
为了检测受噪声污染图像的边缘,提出了一种基于变差函数和方向小波的多尺度边缘检测新方法.首先,在我们前期研究成果的基础上,基于变差函数理论,提出了图像中45度和135度方向边缘的判别准则.然后根据图像中边缘的方向性,选择合适的方向小波旋转参数,再利用方向小波对各个子区域进行不同尺度小波变换.仿真实验表明,对于受高斯白噪声污染的图像,所提出的边缘检测方法无论在边缘定位的准确性还是在去除伪边缘点方面,均优于传统的小波边缘检测方法.
For detecting the edge of noise image, a new multiscale edge detection algorithm based on variogram function and directional wavelet is proposed. First, the criterions for the 45 degree and 135 degree directional edge in a image are proposed based on our previous research results and variogram function theory, respectively. Then, based on the direction of edges, an appropriate rotating parameter of directional wavelet is determined. The directional wavelet transform with different scales at different direction is implemented for different subregion. Thus, not only the accurate edge location is obtained, but also false edge points produced by noise and uneven gray scale in image are removed as much as possible. The results of simulation on the image contaminated badly by Gaussian noise indicate the performance of the proposed algorithm outperform the ones of the exist edge detection approaches with respect to maintaining edge and denoising.
出处
《计算机系统应用》
2012年第9期182-186,共5页
Computer Systems & Applications
关键词
变差函数
边缘检测
方向小波
多尺度分析
图像噪声
variogram function
edge detection
direction wavelet
multiscale analysis
image noise
