摘要
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.
出处
《测绘学报》
EI
CSCD
北大核心
2010年第3期283-288,294,共7页
Acta Geodaetica et Cartographica Sinica
基金
辽宁省自然科学基金(20072156)
辽宁"百千万人才工程"(2008921036)
南京邮电学院图像处理与图像通信江苏省重点实验室开放基金(ZK207008)
关键词
遥感图像
去噪
偏微分方程
高斯与椒盐噪声
混合模型
remote sensing image
de-noising
PDE
Gaussian and salt-pepper noise
hybrid model