摘要
P-M扩散模型是图像处理中用于去噪平滑的经典模型,但在实际应用中常会出现零散的斑点。为了去除残存的噪点,通常采用平滑处理来消除高梯度的噪声,但这又模糊了边缘,损失了细节信息。从此问题入手,采用在噪声图像平滑处理后,应用分数阶微分来锐化图像,由于分数阶微分的非线性特性,此方法可以在增强边缘特征的同时不明显加强噪声信息。实验证明,通过文中方法的处理,图像质量和信噪比都有了明显提升。
P-M diffusion model——a classical image denoising model, has been widely used in image processing. However, some scattered spots, that is, the noisy points would occur in practical application by using this method. In order to remove the noisy point, a generally-used way is to eliminate the noisy point of high gradient by some image smoothing method, this, however, would also cause blurred edges and loss of details. So in this paper, a new image denoising method is proposed, which uses the fractional differential method to sharpen the image after the image smoothing process. By using the nonlinear characteristics of fractional differential, the edge features of the image are enhanced without increasing its noise. Experiment results show that this method could improve both the signal-to-noise ratio （SNR） and the quality of the image.
出处
《通信技术》
2010年第2期74-76,共3页
Communications Technology
关键词
扩散模型
去噪平滑
分数阶微分
图像增强
diffusion model
image denoising and smoothing
fractional differential
image enhancement
