An Image Denoising Method based on Fast Discrete Curvelet Transform and Total Variation

摘要：

In this paper, A new hybrid image denoising method is proposed based on curvelet transform and Total Variatlon(TV) algorithm for removal of addictive white Gaussian noise. Firstly, perform fast discrete curvelet transform using USFFT to the noisy image, then perform hard threshold to the curvelet coefficients of every sub-band and reconstruct the modified coefficients to obtain primary denoised image. In order to remove the surround effect brought by curvelet transform, we conduct further filtering by TV method with about 10 iterations only. The experiment results show that the hybrid algorithm suppress surround effect without appearing staircase effect of TV method effectively. We obtain better visual quality and PSNR comparing to the curvelet transform based method. At the same time, the proposed method takes less computational time than TV filter and achieves better synthesized performance.

关键词： image denoising fast discrete curvelet transform TV filter surround effcet staircase effect

作者: Hongzhi Wang Liying Qian Jingtao Zhao

作者单位: College of Computer Science and Engineering Changchun University of Technology, Changchun, Jilin, 130012,Changchun, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 1040-1043

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）