摘要
基于PDE的非线性扩散滤波对接近高斯分布的噪声消除可取得好的效果,但对于脉冲噪声其效果并不理想。从Perona&Malik模型的扩散系数函数出发,对其函数性质进行分析。通过改进扩散系数函数中的边缘阈值,使其能在消除高梯度图像噪声的同时更好地保持边缘,在一定程序上克服了边缘保持与噪声消除之间的矛盾。
Nonlinear diffusion filter based on Partial Differential Equation （PDE） is good at removing Gauss noises, but do not well at pulse noises. From the diffusion coefficient of Perona ＆ Malik model, the function nature was analyzed. By changing the form of the threshold value in diffusion function, it can get rid of the noises from image while preserving edges better, and overcome the contradictions between keeping edge and eliminating noises.
出处
《计算机应用》
CSCD
北大核心
2007年第8期2025-2026,2029,共3页
journal of Computer Applications
基金
福建省科技计划资助项目(2006Y0042)
关键词
偏微分方程
边缘阈值
噪声消除
图像平滑
Partial Differential Equation （PDE）
threshold value
noises removal
image smoothing
