Multilevel Threshold Based Image Denoising in Curvelet Domain

作     者：Nguyen Thanh Binh Ashish Khare 

作者机构：Department of Electronics and Communication University of Allahabad 

出 版 物：《Journal of Computer Science & Technology》 (计算机科学技术学报（英文版）)

年 卷 期：2010年第25卷第3期

页      面：632-640页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 080203[工学-机械设计及理论] 0835[工学-软件工程] 0802[工学-机械工程] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported in part by the University Grants Commission New Delhi India under Grant No. F.No.36-246/2008(SR) 

主　　题：curvelet transform denoising multilevel thresholding cycle-spinning 

摘      要：In this paper, we propose a multilevel thresholding technique for noise removal in curvelet transform domain which uses cycle-spinning. Most of uncorrelated noise gets removed by thresholding curvelet coefficients at lowest level, while correlated noise gets removed by only a fraction at lower levels, so we used multilevel thresholding on curvelet coefficients. The threshold in the proposed method depends on the variance of curvelet coefficients, the mean and the median of absolute curvelet coefficients at a particular level which makes it adaptive in nature. Results obtained for 2-D images demonstrate an improved performance over other recent related methods available in literature.