Paper Title:
A Novel Denoising Algorithm Based on Fuzzy Clustering and Wavelet Transform
  Abstract

According to analyzing the different wavelet coefficients' transmission property of signals and noises under different scales of the wavelet transform, LEFC denoising algorithm based on fuzzy clustering and wavelet transform is proposed. Our experimental evaluations show that the algorithm is effective and robust to restore the images compared with the other wavelet soft-thresholding algorithms. When the ratio exceeds 40 %, LEFC gives superior performance.

  Info
Periodical
Key Engineering Materials (Volumes 428-429)
Edited by
Yuan Ming Huang
Pages
569-572
DOI
10.4028/www.scientific.net/KEM.428-429.569
Citation
S. Wei, C. J. Ou Yang, S. M. Wei, "A Novel Denoising Algorithm Based on Fuzzy Clustering and Wavelet Transform", Key Engineering Materials, Vols. 428-429, pp. 569-572, 2010
Online since
January 2010
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: De Xiang Zhang, Hong Hai Wang, Jing Jing Zhang
Chapter 3: Data, Text, Sound, Image, Signal and Video Processing and Technologies
Abstract:The contourlet transform is a new two-dimensional extension of the wavelet transform using multiscale and directional filter banks and has...
308
Authors: De Xiang Zhang, Bao Hong Yuan, Jing Jing Zhang
Chapter 5: Numerical Methods, Computation Methods and Algorithms for Modeling, Simulation and Optimization, Data Mining and Data Processing
Abstract:Tetrolets are Haar-type wavelets whose supports are tetrominoes which are shapes made by connecting four equal-sized squares. Firstly, the...
1859