基于Demons算法改进的图像去噪模型研究  

Image denoising model based on the improved Demons algorithm

作　　者：周先春[1,2,3] 汪美玲[1,2,3] 周林锋[1,2,3] 吴琴[1,2,3] 

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]南京信息工程大学气象传感网技术工程中心,南京210044 [3]南京信息工程大学,江苏省气象探测与信息处理重点实验室,南京210044

出　　处：《物理学报》2015年第2期141-150,共10页Acta Physica Sinica

基　　金：国家自然科学基金(批准号:11202106;61302188);教育部高等学校博士学科点专项科研基金(批准号:20123228120005);江苏省"信息与通信工程"优势学科建设项目;江苏省自然科学基金(批准号:BK20131005);江苏省高校自然科学研究项目(批准号:13KJB170016)资助的课题~~

摘　　要：在Demons算法的基础上,将扩散过程看作图像配准,建立一种新的基于图像配准的Demons去噪模型.实验表明,该模型去噪效果优于经典的Perona-Malik模型,排除了模型的病态性.考虑到新模型在图像去噪过程中仅靠梯度信息表示图像的局部特征还不完善,故将水平集曲率作为控制图像结构的驱动力因素引入到此模型中,提出了一种新的梯度和曲率双重驱动力的图像去噪模型.分析和仿真结果表明,两种新模型都可有效抑制噪声,清晰度也有明显的提高,其中双重驱动力的图像去噪模型去噪效果更具优越性.According to image registration, we build a new Demons model of image denoising, in which the diffusion access is regarded as image registration. The experimental results indicate that the performance of the model is better than that of the Perona-Malik model： the ill-condition of the model is removed. It is not enough to describe local characteristics only by using the gradient information in the access of image denoising, so a level set curvature which is the driving force of image structure controlling is introduced into the denoising model. Therefore we propose a new model of image denoising based on two driving forces of gradient and curvature. The simulation results show that the two improved models can both suppress noise effectively, their definitions are enhanced obviously, the performance of image denoising model of two driving forces is more greatly improved.

关 键 词：Demons去噪 Perona-Malik模型 图像配准 水平集曲率 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]