遥感图像高斯与椒盐噪声的PDE混合去噪模型研究

A PDE-based Hybrid Model for De-noising Remote Sensing Image with Gaussian and Salt-pepper Noise

针对经过前期处理的遥感图像主要含有高斯噪声和椒盐噪声的特点,提出一种基于PDE的混合去噪模型,该模型克服传统的纯各向异性扩散模型在平滑区域过度扩散、产生阶梯效应和四阶PDE模型在去噪的同时过多损失边缘信息的弱点,在有效去除遥感图像中混合噪声的同时,很好地保持图像的边缘和纹理细节信息。实验结果验证所提出模型的有效性和稳定性。

A PDE-based hybrid model is proposed to de-noise the pre-processed remote sensing images,which are often polluted by Gaussian and salt-pepper noises.The model solves the excessive diffusion problem at smooth regions and staircase effect presented in traditional pure anisotropic diffusion model.Meanwhile,it overcomes the shortage of 4-order PDE model that tends to lose much edge information.The proposed model can not only efficiently remove mixed noise in remote sensing images,but also simultaneously retain detail information,such as edge and texture.Experimental results illustrate the effectiveness and stability of the proposed model.