期刊文献+

数字双边全变差滤波及非线性去噪 被引量:5

Digital Bilateral TV Filtering and Nonlinear Denoising
下载PDF
导出
摘要 为了更好地滤噪,在研究基于数字滤波器的图像去噪问题的基础上,首先简洁地建立了双边滤波与最优能量泛函之间的理论联系,同时导出一类广义双边滤波器;然后基于双边滤波在阶数大邻域中的双重异性加权滤波机制,推广了Chan提出的数字全变差(TV)模型,提出了一种数字双边TV模型;随后,建立了基于数字双边TV模型的最优能量泛函,并且导出了适于高斯噪声和脉冲噪声两种情形的非线性数字双边全变差滤波器。实验结果显示,无论是在视觉效果方面,还是去噪后图像的峰值信噪比方面,双边全变差滤波都是对双边滤波和全变差滤波极为合理而有效的推广。尤其对于脉冲噪声,该双边全变差滤波的去噪性能明显优于中值滤波器,具有重要的实用价值。 The paper mainly focuses on the problem of filtering-based noise removal. First of all, the theoretical relationship between bilateral filtering and an optimization functional is concisely constructed, and meanwhile with a kind of generalized bilateral filtering derived. Through combining the idea of bilateral filtering with the digital TV model proposed by Chan, a new regularization term is proposed, based on which a unified optimization functional is subsequently constructed in both cases of Gaussian noise and impulse noise. Finally, a digital bilateral TV filtering is deduced by solving the Euler-Lagrange equation of the optimization functional. Experiment results demonstrate that the digital bilateral TV filtering is a reasonable and effective generalization of both the bilateral filtering and digital TV filtering. Especially for the impulse noise, digital bilateral TV filtering behaves much better than Median filtering, and hence it is a good method for the actual application.
出处 《中国图象图形学报》 CSCD 北大核心 2007年第7期1178-1184,共7页 Journal of Image and Graphics
关键词 非线性去噪 稳健估计 双边滤波 全变差 边缘保持 nonlinear denoising, robust estimation, bilateral filtering, total variation, edge-preserving
  • 相关文献

参考文献17

  • 1Tomasi C,Manduchi R.Bilateral filtering for gray and color images[A].In:Proceedings of 6th International Conference Computer Vision[C],New Delhi,India,1998:839-846.
  • 2Rudin L,Osher S,Fatemi E.Nonlinear total variation based noise removal algorithms[J].Physica D,1992,60:259-268.
  • 3Perona P,Malik J.Scale-space and edge detection using anisotropic diffusion[J].IEEE Transactions on Pattern Analysis and Machine Interlligence,1990,12(7):629-639.
  • 4Chan Tony F.The dgital TV filter and nonlinear denoising[J].IEEE Transactions on Image Processing,2001,10(2):231-241.
  • 5Nagao M,Matsuyama T.Edge preserving smoothing[J].Computer Graphics and Image Processing,1979,9(4):394-407.
  • 6Wang DCC,Vagnucci AH,Li C C.A gradient inverse weighted smoothing scheme and the evaluation of its performance[J].Computer Vision,Graphics,and Image Processing,1981,15(2):167-181.
  • 7Himayat N,Kassam S A.Approximate performance analysis of edge preserving filters[J].IEEE Transactions on Signal Processing,1993,41(9):2764-2777.
  • 8HuberPJ.Robust statistics[M].New York:Wiley,1981.
  • 9Cobson D,Vogel C.Convergence of an iterative method for total variation denoising[J].Society for Industrial and Applied Mathematics,Journal of Numerical Analysis,1997,34(5):1779-1791.
  • 10Farsiu Sina,Robinson M D,Elad Michael,et al.Fast and robust multiframe super resolution[J].IEEE Transactions on Image Processing,2004,13(10):1327-1344.

同被引文献28

引证文献5

二级引证文献28

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部