摘要
传统的图像平滑方法在去除噪声的同时往往会破坏边缘、线务、纹理等图像特征,而基于偏微分方程(PDE)的各向异性扩散算法在抑制噪声的同时能够保持这些特征。研究基于PDE的图像去噪平滑算法并对PDE算法的不足作出改进,将其用于图像去噪处理效果非常理想,并在精密光学元件表面疵病识别的实验中取得较好的效果。
The conventional image smoothing methods can eliminate noise as well as smear the image features such as edges, lines and textures, while the anisotropic diffusion algorithm based on Partial Differential Equations（PDE） not only can suppress the noise but also can preserve these features. This paper studies noise smoothing algorithm based on PDE and improves its insufficiency, and the result is very satisfactory by using the algorithm, and is satisfyingly in the precision optics part surface defect recognition experiment.
出处
《计算机工程》
CAS
CSCD
北大核心
2009年第23期222-223,226,共3页
Computer Engineering
关键词
偏微分方程
图像平滑
疵病
Partial Differential Equations（PDE）
image smoothing
defects
