拟合扩散的自适应图像去噪方法  

Adaptive image de-noising method based on fitting diffusion

作　　者：周先春[1,2] 张浩瑀 吴婷 徐新菊[1,2] 翟靖宇 Zhou Xianchun;Zhang Haoyu;Wu Ting;Xu Xinju;Zhai Jinyu(School of Electronic and Information Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China;Jiangsu Collaborative Innovation Center of Atmospheric Environment and EquipmentTechnology,Nanjing University of Information Science and Technology,Nanjing 210044,China)

机构地区：[1]南京信息工程大学电子与信息工程学院,南京210044 [2]南京信息工程大学,江苏省大气环境与装备技术协同创新中心,南京210044

出　　处：《电子测量与仪器学报》2020年第2期97-106,共10页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金(11202106,61302188);江苏省“信息与通信工程”优势学科建设项目;江苏品牌专业建设工程资助项目。

摘　　要：针对纹理等细节信息丢失和图像边缘退化的问题,提出一种拟合扩散的自适应阈值图像去噪算法。首先,改进了扩散方程中的扩散系数,建立拟合扩散系数,克服因扩散强度过大带来的纹理细节信息丢失和边缘退化的弊端;然后,对阈值函数进行了自适应设计和改进,使其根据图像的最大灰度值和迭代次数自动控制阈值,进一步保留图像边缘和细节特征;最后,对新算法进行分析和仿真。实验结果表明,提出的新算法在图像去噪和保边缘、纹理等细节信息方面效果明显,峰值信噪比有了大幅提高,新算法性能优异,有利于实际应用。This paper put forward an adaptive threshold image denoising algorithm based on fitting diffusion to deal with the problem of texture loss and edge degradation. The algorithm will first improve the diffusion coefficient of the diffusion equation, establish fitting diffusion coefficient, avoid filtering incomplete due to the rapid convergence and the problem of image excessive smoothing. Then, the threshold will be designed and improved, and it will be automatically controlled by the maximal image gray value and iterative times, which can keep the image edge and detail features. Last, the designed algorithm will be simulated. The experimental result shows that the proposed algorithm can enhance the performance of de-noising and protection of edge and detail information of texture, the peak Signal to Noise Ratio is promoted drastically. The new algorithm has excellent performance and is beneficial to practical application.

关 键 词：拟合扩散系数 各向异性 P-M模型 偏微分方程 自适应阈值 图像去噪 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] O175.2[自动化与计算机技术—计算机科学与技术]