数据驱动核的非局部均值滤波器改进

doi:10.6040/j.issn.1671-9352.2.2013.128

山东大学学报（理学版）

数据驱动核的非局部均值滤波器改进

孙忠贵1,陈杰2

1.聊城大学数学科学学院, 山东聊城 252000;
2.聊城大学图书馆, 山东聊城 252000

收稿日期:2013-12-13 出版日期:2014-05-20 发布日期:2014-06-04

Improvement for non-local means using data driven kernel

SUN Zhong-gui1, CHEN Jie2

1. Department of Mathematics Science, Liaocheng University, Liaocheng 252000, Shandong, China;
2. Library of Liaocheng University, Liaocheng 252000, Shandong, China

Received:2013-12-13 Online:2014-05-20 Published:2014-06-04

摘要/Abstract

摘要： 通过对非局部均值滤波器进行模型分析,发现其在一定程度上仍具有各向同性的缺陷,进而提出了一个数据依赖的改进滤波器算法。与原有算法相比,该算法采用数据驱动核对图像片加权,得到了更好的去噪效果。

关键词: 核方法, 数据驱动, 非局部均值滤波, 图像去噪

Abstract: The isotropy defect of non-local means (NLM) was pointed out with the help of model analysis. Further, an improved version of NLM was developed to compensate such a weakness. Compared with the original one, the new version based on the data driven kernel and encouraging experimental results are exhibited.

Key words: image denoising, non-local means, data-driving, kernel methods

孙忠贵1,陈杰2. 数据驱动核的非局部均值滤波器改进[J]. 山东大学学报（理学版）, 2014, 49(05): 24-27.

SUN Zhong-gui1, CHEN Jie2. Improvement for non-local means using data driven kernel[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2014, 49(05): 24-27.

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[1]	王鹏鸣,钟茂生,刘遵雄. 去噪空间上的多核学习[J]. J4, 2012, 47(5): 49-52.
[2]	曾文赋1,黄添强1,2,李凯1,余养强1,郭躬德1,2. 基于调和平均测地线核的局部线性嵌入算法[J]. J4, 2010, 45(7): 55-59.
[3]	万海平,何华灿,周延泉 . 局部核方法及其应用[J]. J4, 2006, 41(3): 18-20 .

数据驱动核的非局部均值滤波器改进

Improvement for non-local means using data driven kernel

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