Denoising of Images Using Locally Adaptive Wiener Filter in Wavelet Domain
Summary :
In this paper, a Wiener filtering method in wavelet domain is proposed for restoring an image corrupted by additive white noise. The proposed method utilizes the multiscale characteristics of wavelet transform and the local statistics of each subband. The size of a filter window for estimating the local statistics in each subband varies with each scale. The local statistics for every pixel in each wavelet subband are estimated by using only the pixels which have a similar statistical property. Experimental results show that the proposed method has better performance over the Lee filter with a window of fixed size.
- Publication
- IEICE TRANSACTIONS on Information Vol.E84-D No.4 pp.495-501
- Publication Date
- 2001/04/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Image Processing, Image Pattern Recognition
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Ick-Hoon JANG, Nam-Chul KIM, "Denoising of Images Using Locally Adaptive Wiener Filter in Wavelet Domain" in IEICE TRANSACTIONS on Information,
vol. E84-D, no. 4, pp. 495-501, April 2001, doi: .
Abstract: In this paper, a Wiener filtering method in wavelet domain is proposed for restoring an image corrupted by additive white noise. The proposed method utilizes the multiscale characteristics of wavelet transform and the local statistics of each subband. The size of a filter window for estimating the local statistics in each subband varies with each scale. The local statistics for every pixel in each wavelet subband are estimated by using only the pixels which have a similar statistical property. Experimental results show that the proposed method has better performance over the Lee filter with a window of fixed size.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_4_495/_p
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@ARTICLE{e84-d_4_495,
author={Ick-Hoon JANG, Nam-Chul KIM, },
journal={IEICE TRANSACTIONS on Information},
title={Denoising of Images Using Locally Adaptive Wiener Filter in Wavelet Domain},
year={2001},
volume={E84-D},
number={4},
pages={495-501},
abstract={In this paper, a Wiener filtering method in wavelet domain is proposed for restoring an image corrupted by additive white noise. The proposed method utilizes the multiscale characteristics of wavelet transform and the local statistics of each subband. The size of a filter window for estimating the local statistics in each subband varies with each scale. The local statistics for every pixel in each wavelet subband are estimated by using only the pixels which have a similar statistical property. Experimental results show that the proposed method has better performance over the Lee filter with a window of fixed size.},
keywords={},
doi={},
ISSN={},
month={April},}
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TY - JOUR
TI - Denoising of Images Using Locally Adaptive Wiener Filter in Wavelet Domain
T2 - IEICE TRANSACTIONS on Information
SP - 495
EP - 501
AU - Ick-Hoon JANG
AU - Nam-Chul KIM
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2001
AB - In this paper, a Wiener filtering method in wavelet domain is proposed for restoring an image corrupted by additive white noise. The proposed method utilizes the multiscale characteristics of wavelet transform and the local statistics of each subband. The size of a filter window for estimating the local statistics in each subband varies with each scale. The local statistics for every pixel in each wavelet subband are estimated by using only the pixels which have a similar statistical property. Experimental results show that the proposed method has better performance over the Lee filter with a window of fixed size.
ER -
English
