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基于PDE算法的指静脉图像预处理
引用本文:张凤春,于思瑶,郭树旭.基于PDE算法的指静脉图像预处理[J].吉林大学学报(理学版),2012,50(3):552-556.
作者姓名:张凤春  于思瑶  郭树旭
作者单位:吉林大学 电子科学与工程学院, 长春 130012
基金项目:吉林省科技发展计划项目,吉林大学基本科研业务费
摘    要:为了更好地去除手指静脉图片中的噪声, 提出一种基于偏微分方程算法(PDE)的去噪新模型. 该模型在P M模型的基础上, 采用新的扩散函数, 并结合四阶PDE模型对原模型结构进行变换. 用合成图像和真实指静脉图像分别对新模型进行实验验证, 结果表明, 相对于P M模型, 新模型使信噪比(SNR)值提高了约5 dB, 且能在去除噪声的同时很好地保持指静脉特征.

关 键 词:偏微分方程(PDE)    图像去噪    P  M模型  信噪比(SNR)  
收稿时间:2011-06-04

Preprocessing of Finger Vein Image Based on PDEs
ZHANG Feng-chun , YU Si-yao , GUO Shu-xu.Preprocessing of Finger Vein Image Based on PDEs[J].Journal of Jilin University: Sci Ed,2012,50(3):552-556.
Authors:ZHANG Feng-chun  YU Si-yao  GUO Shu-xu
Institution:College of Electronic Science and Engineering, Jilin University, Changchun 130012, China
Abstract:According to the characteristics of finger vein image,a new denoising model based on partial differential equations was presented.This model uses the new diffusion function based on the traditional P-M model,and combines with fourth-order partial differential equations model to transform the original model structure.The performance of the new model is verified by both synthetic and real finger vein images.It shows that the new model could increase the signal-to-noise ratio up 5 dB and maintain the features of finger vein image better compared with the original model.
Keywords:partial differential equations(PDE)  image denoising  P-M model  signal-to-noise ratio(SNR)
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