基于分数阶微分算子与高斯曲率相结合的自适应图像去噪

Adaptive image denoising based on fractional differential operator and Gauss curvature

文中提出分数阶微分算子和高斯曲率相结合的自适应图像去噪方法。将高斯曲率引入偏微分方程模型中,由图像梯度进行边缘检测,再结合高斯曲率和分数阶微分算子的性质,由图像的局部方差建立分数阶微分算子,构建基于分数阶微分算子的自适应图像去噪模型,进行自适应地扩散去噪。结果表明,新算法性能优异,内部信息保护更具完整性,有利于实际应用。

An adaptive image denoising method combining Gauss curvature with fractional differential operator is proposed in this paper.The Gauss curvature is introduced into the partial differential equation model,and the image edge is detected by the image gradient.In combination with the properties of the Gauss curvature and fractional differential operator,the fractional differential operator is established by means of the local variance of the image.An adaptive image denoising model based on fractional differential operator is constructed to carry out adaptive diffusion denoising.The results show that the new algorithm has better performance and can protect internal information more entirely,which is beneficial to practical application.