Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (28): 178-180.DOI: 10.3778/j.issn.1002-8331.2010.28.050

• 图形、图像、模式识别 • Previous Articles     Next Articles

Non-Local Means algorithm based on structure tensor

XU Juan1,2,SUN Yu-bao2,WEI Zhi-hui2   

  1. 1.School of Mathematics and Computing Science,Anqing Teachers College,Anqing,Anhui 246011,China
    2.School of Science,Nanjing University of Science and Technology,Nanjing 210094,China
  • Received:2009-05-05 Revised:2009-06-22 Online:2010-10-01 Published:2010-10-01
  • Contact: XU Juan

基于结构张量的Non-Local Means去噪算法研究

许 娟1,2,孙玉宝2,韦志辉2   

  1. 1.安庆师范学院 数学与计算科学学院,安徽 安庆 246011
    2.南京理工大学 理学院,南京 210094
  • 通讯作者: 许 娟

Abstract: Non-Local Means(NL-Means) algorithm is an emerging and effective image denoising method.In order to sufficiently use the self-similarity of the image local geometric structures,this paper proposes a NL-Means image denoising algorithm based on structure tensor for similarity measure,which is capable of describing the self-similarity of local geometric structures in the image.The experimental results demonstrate the effectiveness of the algorithm,also show that the method has advantages for both edge preserving and PSNR value.

Key words: image denoising, Non-Local Means(NL-Means) algorithm, structure tensor, local contrast

摘要: 非局部平均是当前一种新兴而有效的图像去噪方法。为了能充分利用数字图像局部几何结构的自相似性,同时由于结构张量可有效刻画数字图像的局部几何结构特征,进而提出了基于结构张量相似性度量的非局部平均去噪算法。实验结果验证了该算法抑制噪声的有效性,同时能很好地保持边缘等细节特征,峰值信噪比得到有效提高。

关键词: 图像去噪, 非局部均值算法, 结构张量, 局部对比度

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