保边缘自蛇模型毫米波图像去噪  

New edge-preserving self-snake model for millimeter wave image denoising

作　　者：颜廷秦[1,2] 周昌雄[1] 苏品刚[1] 尚丽[1] 

机构地区：[1]苏州市职业大学电子信息工程系,江苏苏州215104 [2]苏州市数字化设计与制造技术重点实验室,江苏苏州215104

出　　处：《计算机工程与应用》2014年第9期160-162,175,共4页Computer Engineering and Applications

基　　金：国家自然科学基金(No.60970058);江苏省自然科学基金(No.BK2009131);江苏省青蓝工程项目;苏州市科技基础设施建设计划项目(No.SZS201009);苏州市职业大学创新团队建设项目(No.3100125)

摘　　要：由于毫米波图像分辨率低并伴随有大量噪声,其图像边缘常被噪声污染或丢失,为此提出保边缘自蛇模型并应用于毫米波图像去噪。引入只在图像的边缘处具有最大值,且对噪声不敏感的非局部梯度,以此构造边缘停止函数,使其在图像边缘处接近0,而在平坦同质区域接近1;给出保边缘的自蛇模型迎风差分数字解法;提出毫米波图像去噪的定量评价算法性能指标。实验结果表明,该算法在等效视数和边缘清晰度性能指标上明显优于标准自蛇模型和保特征的各向异性扩散模型,具有较好的去噪效果和保边缘能力。For millimeter wave image having a lower resolution and a lot of noises, edges are partly lost to a certain extent or contaminated severely by noise. In this paper, a new edge-preserving self-snake model for the millimeter wave image de-noise is presented. The edge stopping function which is approximated to zero around fine structures and is close to one in the interior of homogeneous regions is constructed with the non-local gradient having maximum peak only at edges and good tolerance for noise. A discrete algorithm for proposed model is given with upwind differential scheme. The quantitative evaluation of performance is also defined. In visual quality and the performance of ENL（Equivalent Number of Looks） and edge definition, the experiment results show that this algorithm is better than conventional self-snake model, and feature-preserving nonlinear anisotropic diffusion.

关 键 词：非局部梯度 自蛇模型 保边缘 毫米波图像 边缘停止函数 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]