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

Content Provider	IEEE Xplore Digital Library
Author	Zhang Fengjun Xie Chengjun Yin Jianhui Zhou Zhiqiang
Copyright Year	2011
Description	Author affiliation: College of Computer Science and Technology of Beihua University, JiLin, China (Zhang Fengjun; Xie Chengjun; Yin Jianhui) \|\| Retired Administrative Office in JiLin of ShenYang, Railways Bureau, JiLin, China (Zhou Zhiqiang)
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.
Starting Page	1090
Ending Page	1093
File Size	723293
Page Count	4
File Format	PDF
ISBN	9781612847191
e-ISBN	9781612847221
DOI	10.1109/MEC.2011.6025656
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stationary wavelet Prior dstribution PSNR Noise reduction Threshold denoising Noise measurement Mallat algorithm Multiresolution analysis Wavelet coefficients Image denoising
Content Type	Text
Resource Type	Article

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