期刊文献+

基于图像边缘检测的小波阈值去噪方法 被引量:1

Wavelet threshold denoising method based on image edge detection
下载PDF
导出
摘要 提出一种基于图像边缘检测的小波阈值去噪新方法。该方法利用Canny算子检测出图像的边缘,进而定义了一种新的阈值函数,然后对含噪图像、边缘图像的小波变换系数采用新阈值函数分别进行阈值处理,将处理后的边缘图像与图像的小波系数进行融合,得到去噪后的图像。实验结果表明,采用该方法处理的去噪图像,能够在去噪的同时有效地保持图像的边缘信息。 The image denoising method based on edge detection and wavelet threshold is proposed.This method is to use Canny operator to detect the edge of the image,and defines a new threshold function.The noised image and the image edge are denoised by a new wavelet threshold method and finally the denoised image is obtained by fusing the wavelet denoised image and the edge image.Experiment results show that the method can effectively keep image′s edges and excels commonly-used wavelet threshold denoising methods.
出处 《天津工程师范学院学报》 2009年第4期23-25,共3页 Journal of Tianji University of Technology and Education
基金 天津市自然科学基金资助项目(08JCYBJC12100)
关键词 小波变换 图像去噪 边缘检测 阈值函数 wavelet transform image denoising edge detection threshold function
  • 相关文献

参考文献5

二级参考文献15

  • 1蒋东方,陈明.一种实时小波降噪算法[J].仪器仪表学报,2004,25(6):781-783. 被引量:33
  • 2代广进,侯正信.小波域信号去噪算法[J].电子测量技术,2005,28(6):37-37. 被引量:6
  • 3曾理,安贝贝,马睿.脊波在工业CT图像裂纹边缘检测中的应用[J].仪器仪表学报,2007,28(6):981-986. 被引量:13
  • 4Mallat S. A theory for multiresolution signal decomposition: The wavelet representation[J]. IEEE Transactions on Pattern Analysis and Machine InteUigenoe, 1989,11 (7) : 674 - 693.
  • 5Donoho D L, Johnstone I M. Ideal Spatial Adaptation Via Wavelet Shrinkage[ J ]. Biometrika, 1994,81 ( 12 ) : 425 - 455,
  • 6Donoho D L. Denoising by Soft - thresholding[ J ]. IEEE Trans on IT,1995,41(3) :613- 627.
  • 7DONOHO D L, DUNCAN M R. Digital eurvelet transform. Strategy, implementation and experiment[C]. Proe. SHE. San Jose, CA: SPIE Press, 2000: 12-30.
  • 8CANDES E J,DONOHO D L. Curvelets [R]. USA.. Department of Statistics, Stanford University, 1999.
  • 9CANDES E J. Ridgelets: Theory and applications [D ]. Department of Statistics, Stanford University, 1998.
  • 10STARCK J L, CANDES E J, DONOHO D L. The Curvelet transform for image denoising [J].IEEE Trans Image Processing, 2002,11 (6) : 670-684.

共引文献148

同被引文献21

引证文献1

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