A Novel Image Correlated Noise Reduction Method Based on Multiwavelet Transformation

Author

Di, Xiaoguang ; Zhou, Fengqi ; Yao, Yu ; Fu, Shaowen

Author_Institution

Control & Simulation Center, Harbin Inst. of Technol.

Volume

2

fYear

0

fDate

0-0 0

Firstpage

9862

Lastpage

9866

Abstract

A novel stationary multiwavelet transform (SMWT) method is proposed. The method possesses the good quality of both multiwavelet transform and stationary scalar wavelet transform on image denoising. Being redundant, the SMWT can decorrelate the image and noise. The Mallat decomposition and reconstruction of 2D image based on SMWT was inferred. By level-dependent thresholding the SMWT coefficients of image with correlated noise, the image with high quality could be reconstructed. The simulation results show the effect of correlated noise reduction based on this method has obvious superiority compared with scalar wavelet and general multiwavelet transformation method. At the same time, the recovery image can preserve as many the characteristics of original image as possible

Keywords

decorrelation; image denoising; image reconstruction; wavelet transforms; 2D image reconstruction; Mallat decomposition; decorrelation; image correlated noise reduction; image denoising; image recovery; level-dependent thresholding; stationary multiwavelet transform; stationary scalar wavelet transform; Automation; Decorrelation; Educational institutions; Image denoising; Image reconstruction; Intelligent control; Noise level; Noise reduction; Space technology; Wavelet transforms; correlated noise reduction; level-dependant threshold processing; stationary multiwavelet transformation;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713923

Filename

1713923