Stationary wavelet denoising based on wavelet coefficients obeying prior distribution in subbands

Author

Zhang Fengjun ; Xie Chengjun ; Yin Jianhui ; Zhou Zhiqiang

Author_Institution

Coll. of Comput. Sci. & Technol., Beihua Univ., Jilin, China

fYear

2011

fDate

19-22 Aug. 2011

Firstpage

1090

Lastpage

1093

Abstract

Edge distortion in image denoising can be improved effectively based on Stationary Wavelet Transformation (SWT) instead of Orthogonal Wavelet Transformation (OWT). The statistics of wavelet coefficients in subbands can be supposed obeying a Prior Distribution Model (PDM), through which the threshold function with ideal shrinkage can be deduced and improve image denoising in the smooth regions effectively. The method based on SWT combining with PDM proposed in this paper can improve both Peak Signal to Noise Ratio (PSNR) and visual effect of the image denoised through Matlab simulation experiments.

Keywords

image denoising; mathematics computing; wavelet transforms; Matlab simulation; edge distortion; ideal shrinkage; image denoising; peak signal to noise ratio; prior distribution model; stationary wavelet denoising; stationary wavelet transformation; subbands; threshold function; visual effect; Image denoising; Multiresolution analysis; Noise measurement; Noise reduction; PSNR; Wavelet coefficients; Mallat algorithm; prior dstribution; stationary wavelet; threshold denoising;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on

Conference_Location

Jilin

Print_ISBN

978-1-61284-719-1

Type

conf

DOI

10.1109/MEC.2011.6025656

Filename

6025656