一种改进的双项自适应总体变差去噪模型  

An Improved Double-term Adaptive Total Variation De-noising Model

作　　者：储诚曦[1] 李均利[1,2] 李刚[1] 楼洋[1] 

机构地区：[1]宁波大学数字技术与应用软件研究所,浙江宁波315211 [2]四川师范大学计算机科学学院,成都610066

出　　处：《计算机工程》2012年第22期194-197,共4页Computer Engineering

基　　金：国家自然科学基金资助项目(60672072);宁波市自然科学基金资助项目(2009A610089)

摘　　要：研究经典总体变差去噪模型及其改进的自适应去噪模型,提出一种基于预处理图像局部信息的双项自适应模型。利用空间自适应保真项缓解二阶非线性滤波对细节的过度平滑,通过自适应正则化项减少阶梯效应,使数值更稳定和收敛。实验结果表明,与原方法相比,改进方法具有更好的鲁棒性,在噪声较高的情况下仍能取得较好的去噪效果。On the base of the classic total variation de-noising model and its improved models, this paper proposes an improved double-entry adaptive Total Variation（TV） model based on local information of pre-made images. An adaptive spatial fidelity term is intended to ease the smoothing effect by the second-order nonlinear filtering over the details. An adaptive regularization term is to further reduce the staircase effect, also to achieve a more stable and convergence value. Experimental results show that the improved method still can achieve better results in high noise. Compared with the original method, it has better noise robustness.

关 键 词：图像去噪 阶梯效应 自适应保真项 自适应正则化项 残差图像 平均梯度 

分 类 号：TN911.73[电子电信—通信与信息系统]