The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Neste artigo, um método de filtragem de Wiener no domínio wavelet é proposto para restaurar uma imagem corrompida por ruído branco aditivo. O método proposto utiliza as características multiescala da transformada wavelet e as estatísticas locais de cada sub-banda. O tamanho de uma janela de filtro para estimar as estatísticas locais em cada subbanda varia de acordo com cada escala. As estatísticas locais para cada pixel em cada subbanda wavelet são estimadas usando apenas os pixels que possuem uma propriedade estatística semelhante. Resultados experimentais mostram que o método proposto apresenta melhor desempenho em relação ao filtro de Lee com janela de tamanho fixo.
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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 -