期刊文献+

频谱包络滤波器及其应用 被引量:2

Spectrum Envelope Filter and Application
下载PDF
导出
摘要 针对图像处理中的保边平滑问题,提出了一种新的保边平滑滤波器.滤波器通过分析自然图像的频谱特性以及背景噪声在图像频谱中的分布规律,将图像频谱分为对重构图像边缘起重要作用的能量聚集区和背景噪声区.先用傅里叶变换计算输入图像的频谱,滤波时的滤波器通过模拟自然图像的频谱包络来修正该频谱,这样在保留能量聚集区中的频率的同时抑制背景噪声区中的频率,使得滤波后的图像仍然具有原始图像频谱的显著特征,而修正后的频谱经过傅里叶逆变换可以重构图像.实验结果表明,所提滤波器在平滑背景噪声的同时,能够更好地保护原始图像的边缘信息,保边性能优于传统高斯滤波器,滤波结果的视觉效果也明显优于均值漂移滤波器. A new edge preserving filter is proposed for the edge protection when the background noise is smoothing during image processing.The filter classifies the image spectrum into two areas by analyzing the spectrum characteristics of natural images and the distribution of background noise in image spectrum:one is the energy-concentrated area that plays an important part in rebuilding the edges;and the other is the background noise area.The spectrum of an imported image is calculated by the Fourier transformation.The spectrum is modified during filtering by the filter which gets correction factors by simulating the spectrum envelope of nature image so that the frequency of energy-concentrated area can be preserved and that of background noise area can be restrained.The filtered image still holds the main characteristic of original spectrum,which can be calculated from the modified spectrum using the inverse Fourier transformation.Experimental results show that the proposed filter can well protect the edge information of original image when the background noise is smoothing,has better performances than the traditional Gaussian filter in edge preserving,and creates a better subjective impression than the mean-shift filter.
出处 《西安交通大学学报》 EI CAS CSCD 北大核心 2010年第8期48-52,共5页 Journal of Xi'an Jiaotong University
基金 国家自然科学基金资助项目(60805015)
关键词 图像平滑 背景噪声 边缘保持 频谱 image smooth background noise edge preserving spectrum
  • 相关文献

参考文献11

  • 1WANG Bin,ROSE D M,FARAG A A,et al.Localestimation of Gaussian-based edge enhancement filters using Fourier analysis[C] //IEEE International Conference on Acoustics,Speech,and Signal Processing.Minneapolis,MN,USA:ICASSP,1993:13-16.
  • 2DENG G,CAHILL L W.An adaptive Gaussian filter for noise reduction and edge detection[C] //Proceedings of IEEE International Conference on Nuclear Science Symposium and Medical Imaging.Piscataway,NJ,USA:IEEE,1993:1615-1619.
  • 3IZQUIERDO M E,GHANBARI M.Texture smoothing and object segmentation using feature-adaptive weighted Gaussian filtering[C] //ITS'98 Proceedings.Piscataway,NJ,USA:IEEE,1998,650-655.
  • 4IZQUIERDO M E,GHANBARI M.Nonlinear Gaussian filtering approach object segmentation[J].IEE Proceedings of Vision,Image and Signal Processing,1998(3):137-143.
  • 5GEUSEBROEK J M,SMEULDER A W M.Fast anisotropic Gauss filtering[J].IEEE Trans on Image Processing,2003,12(8):938-943.
  • 6UENG S K,CHENG H P,LU R Y.An adaptive Gauss filtering method[J].IEEE Pacific Visualization Symposium.Piscataway,NJ,USA:IEEE,2008:127-134.
  • 7GONZALEZ R C,WOODS R E.Digital image processing[M].2nd ed.Beijing,China:Publishing House of Electronics Industry,2007:123-124.
  • 8CHENG Yizong.Mean shift:mode seeking,and clustering[J].IEEE Trans on Pattern Analysis and Machine Intelligence,1995,17(8):790-799.
  • 9LIU Wei,DUAN Yubo,SHAO Keyong,et al.Inage smoothing based on the mean shift algorithm[C] //IEEE International Conference on Control and Automation.Piscataway,NJ,USA:IEEE,2007:1349-1353.
  • 10POIRSON A B,WANDELL B A.The appearance of colored patterns:pattern-color separability[J].Journal of the Optical Society of America:A,1993,10(12):2458-2470.

同被引文献19

  • 1张光玉,解梅,马争.一种新的彩色图像边缘检测算法[J].电子科技大学学报,2005,34(2):164-167. 被引量:10
  • 2高丽,杨树元,夏杰,王诗俊,梁军利,李海强.基于标记的Watershed图像分割新算法[J].电子学报,2006,34(11):2018-2023. 被引量:34
  • 3钟鑫,付俐.一种基于Canny算法的自适应边缘提取方法[J].科学技术与工程,2007,7(16):4067-4069. 被引量:8
  • 4章毓晋.图像分割[M].北京:科学出版社,2001..
  • 5李牧,闫继红,李戈,赵杰.自适应Canny算子边缘检测技术[J].哈尔滨工程大学学报,2007,28(9):1002-1007. 被引量:89
  • 6Canny J,A computational approach to edge detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986,8(6) : 678-698.
  • 7李华强,喻擎苍,方玫.Canny算子中Otsu闽值分割法的运用[J].行算机工程与设计.2008,29(9):2297-2299.
  • 8Perter I R,Yang Zhang.The Bayesian operating point of the Canny edge detector[J].IEEE Transactions on hnage Processing, 2006, 15( 11 ) :3409-3416.
  • 9Gonzalez R C, Woods R E.Digital image processing[M]. 2nd ed.Beijing, China: Publishing House of Electronics Industry, 2007 : 123-124.
  • 10Greenspan H, Ruf A, Goldberqer J.Constrained Gaussian mixture model framework for automatic segmentation of MR brain images[J].IEEE Transactions on Medical Imaging, 2006,25 (9).

引证文献2

二级引证文献2

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