基于分数阶变分的图像泊松去噪模型  

Improved image poisson denoising model based on fractional variation

作　　者：胡学刚[1,2] 李妤[1] 

机构地区：[1]重庆邮电大学计算机科学与技术学院,重庆400065 [2]重庆邮电大学系统理论研究及其应用中心,重庆400065

出　　处：《计算机应用》2013年第4期1100-1102,共3页journal of Computer Applications

基　　金：国家自然科学基金资助项目(11071266);重庆市教委科研基金资助项目(KJ100505)

摘　　要：为了进一步提高图像去噪的效果,针对图像泊松噪声的特点,提出了一种有效的基于分数阶导数的图像泊松去噪的变分模型。该模型继承了全变分模型去噪效果良好的优点,并且很好地利用分数阶微分特有的幅频特性优势,在处理图像细节和纹理特征方面很好的保留了图像的"弱信息"。数值实验结果表明,该分数阶变分方法的去噪效果优于传统的整数阶变分方法,能很好地保留图像的边缘细节特征。An effective Poisson denoising model based on fractional derivative for images with Poisson noise was proposed to improve the denoising effect.The model inherited the advantages of total variation model to eliminate noise.Furthermore,due to the advantage of property of amplitude-frequency in fractional differentiation,it can protect ＂weak information＂ well in processing specifics of image and texture characteristics.The numerical experimental results demonstrate that the proposed method of fractional variation to eliminate noise is better than traditional integer variation and can protect the detail characteristics of image edges.

关 键 词：泊松噪声 全变分方法 分数阶微分 图像去噪 边缘细节 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]