期刊文献+

图像去噪中的纹理保护方法研究 被引量:2

Studies on Texture Preserving Image Denoising Methods
下载PDF
导出
摘要 基于偏微分方程及变分极值最小化的图像平滑方法可以有效地去除噪声,而且能够保护边缘信息,但由于噪声及纹理难以区分,使得纹理信息无法保留。提出一种纹理保护滤波算法,该算法利用图像分解模型将图像分解为几何结构分量及噪声/纹理分量,计算后者的局部方差,与传统变分能量最小化方法中的偏差惩罚项结合形成随纹理变化的约束,得到的模型在纹理区域滤波减少,从而保护了纹理信息。实验在视觉效果上得到了预期的结果,信噪比的计算对比也可以证明算法的有效性。 Image smoothing algorithms based on PDE and variational formulation minimization can denoise effectively while preserving the edge information, but the texture information can not be kept as the noise and texture are difficult to discriminate. A new texture preserving filter is proposed. The new algorithm first uses image decomposition model to separate image into the geometry part and the noise/texture part, then calculates the local variance of the latter which is incorporated with the traditional deviation cost to form a spatially adaptive constraint. The new filter smoothes less in the texture regions, thus could preserve the texture information. The visual effect and data analysis of the experiment result proves the effectiveness of the algorithm.
作者 姚伟 孙即祥
出处 《中国图象图形学报》 CSCD 北大核心 2010年第5期723-728,共6页 Journal of Image and Graphics
关键词 纹理保护 滤波局部方差 自适应约束 图像分解 texture preserving filter, local variance, adaptive constraint, image decomposition
  • 相关文献

参考文献27

  • 1Rudin L,Osher S,Fatemi E.Nonlinear total variation based noise removal algorithms[J].Physica D,1992,60(1-4):259-268.
  • 2Blanc-Feraud L,Charbonnier P,Aubert G,et al.Nonlinear image processing:modelling and fast algorithm for regularization with edge detection[C]//Proceedings of the International Conference on Image Processing.Washington:IEEE Computer Society Press,1995,1:474-477.
  • 3Sapiro G,Ringach D.Anisotropic diffusion of multivalued images with applications to color filtering[J].IEEE Transactions on Image Processing,1996,5(11):1582-1586.
  • 4Blomgren P,Chan T.Color TV:Total variation methods for restoration of vector-valued images[J].IEEE Transactions on Image Processing,1998,7(3):304-309.
  • 5Kimmel R,Malladi R,Sochen N.Images as embedded maps and minimal surfaces:movies,color,texture,and volumetric medical images[J].International Journal of Computer Vision,2000,39(2):111-129.
  • 6Strong D,Chan T.Edge-preserving and scale-dependent properties of total variation regularization[J].Inverse Problems,2003,19(6):165-187.
  • 7Mrazek P.Selection of optimal stopping time for nonlinear diffusion filtering[J].International Journal of Computer Vision,2003,52(2/3):189-203.
  • 8Chan T,Wong C.Total variation blind deconvolution[J].IEEE Transactions on Image Processing,1998,7(3):370-375.
  • 9Meyer Y.Oscillating Patterns in Image Processing and in Some Nonlinear Evolution Equations[M]//The Fifteenth Dean Jacquelines B Lewis Memorial Lectures.Boston:American Mathematical Society,2001.
  • 10Aujol J F,Gilboa G,Chan T,et al.Structure-texture image decomposition-modeling,algorithms and parameter selection[J].International Journal of Computer Vision,2006,67(1):111-136.

同被引文献31

  • 1Ibrahim S, Sadhar A, Rajapalan N. Restoration of scanned photographic images.Signal Processing,2006(86): 1035-1048.
  • 2Rudin L, Osher S, Fatemi E. Nonlinear total variation based noise removal algorithms. Physica D, 1992,60(1-4):259-268.
  • 3Meyer Y. Oscillating Patterns in Image Processing and in Some Nonlinear Evolution Equations. The Fifteenth Dean Jacquelines B Lewis Memorial Lectures. Boston: American Mathematical Society, 2001.
  • 4Gilboa G, Sochen N, Zeevi YY. Variational denoising of partly-textured images by spatially varying constraints. IEEE Trans. on Image Processing, 2006,15(8):2281-2289.
  • 5Lysaker M, Lundervold A, Tal XC. Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time. IEEE Trans. on Image Processing, 2003,12(12):1579-1590.
  • 6王郑耀.数字图像的边缘检测[D].西安交通大学:2003.
  • 7LOGAN J R, BENJAMIN F. Infomlation in the zero crossings of bandpass signal [J]. Bell System Technical Journal, 1977, 56(4) :487-510.
  • 8MARR D C, HILDRETH E. Theory of edge detection [J].Proceedings of the Royal Society of London, 1980, 207 : 187-217.
  • 9JAMES H Elder. Are edges incomplete[ J ]. International Journal of Computer Vision, 1999, 34:97-122.
  • 10EMIN YUKSEL M. Edge detection in noisy images by neu-ro-fuzzy processing[ J]. International Journal of Elec- tronics and Communications,2007, 61:82-89.

引证文献2

二级引证文献1

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