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, são introduzidos filtros quase gaussianos, filtros quase medianos e filtros localmente adaptativos. Um novo filtro vetorial adaptativo baseado na estimativa de ruído é proposto para suprimir ruído gaussiano e/ou de impulso. Para estimar o tipo e o grau de corrupção de ruído, um detector de ruído e um detector de bordas são introduzidos, e dois parâmetros principais são obtidos para caracterizar o ruído na imagem colorida. Depois de estimar globalmente o tipo e o grau de corrupção de ruído, diferentes filtros adaptativos localmente são escolhidos adequadamente para aprimoramento de imagem. Todas as imagens com ruído, utilizadas para testar filtros em experimentos, são geradas pelos softwares PaintShopPro e Photoshop. Os resultados experimentais mostram que o novo filtro adaptativo tem melhor desempenho na supressão de ruído e na preservação de detalhes do que o filtro do software Photoshop e outros filtros.
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Mei YU, Gang Yi JIANG, Dong Mun HA, Tae Young CHOI, Yong Deak KIM, "New Adaptive Vector Filter Based on Noise Estimate" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 6, pp. 911-919, June 1999, doi: .
Abstract: In this paper, quasi-Gaussian filter, quasi-median filter and locally adaptive filters are introduced. A new adaptive vector filter based on noise estimate is proposed to suppress Gaussian and/or impulse noise. To estimate the type and degree of noise corruption, a noise detector and an edge detector are introduced, and two key parameters are obtained to characterize noise in color image. After globally estimating the type and degree of noise corruption, different locally adaptive filters are properly chosen for image enhancement. All noisy images, used to test filters in experiments, are generated by PaintShopPro and Photoshop software. Experimental results show that the new adaptive filter performs better in suppressing noise and preserving details than the filter in Photoshop software and other filters.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_6_911/_p
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@ARTICLE{e82-a_6_911,
author={Mei YU, Gang Yi JIANG, Dong Mun HA, Tae Young CHOI, Yong Deak KIM, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={New Adaptive Vector Filter Based on Noise Estimate},
year={1999},
volume={E82-A},
number={6},
pages={911-919},
abstract={In this paper, quasi-Gaussian filter, quasi-median filter and locally adaptive filters are introduced. A new adaptive vector filter based on noise estimate is proposed to suppress Gaussian and/or impulse noise. To estimate the type and degree of noise corruption, a noise detector and an edge detector are introduced, and two key parameters are obtained to characterize noise in color image. After globally estimating the type and degree of noise corruption, different locally adaptive filters are properly chosen for image enhancement. All noisy images, used to test filters in experiments, are generated by PaintShopPro and Photoshop software. Experimental results show that the new adaptive filter performs better in suppressing noise and preserving details than the filter in Photoshop software and other filters.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - New Adaptive Vector Filter Based on Noise Estimate
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 911
EP - 919
AU - Mei YU
AU - Gang Yi JIANG
AU - Dong Mun HA
AU - Tae Young CHOI
AU - Yong Deak KIM
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E82-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 1999
AB - In this paper, quasi-Gaussian filter, quasi-median filter and locally adaptive filters are introduced. A new adaptive vector filter based on noise estimate is proposed to suppress Gaussian and/or impulse noise. To estimate the type and degree of noise corruption, a noise detector and an edge detector are introduced, and two key parameters are obtained to characterize noise in color image. After globally estimating the type and degree of noise corruption, different locally adaptive filters are properly chosen for image enhancement. All noisy images, used to test filters in experiments, are generated by PaintShopPro and Photoshop software. Experimental results show that the new adaptive filter performs better in suppressing noise and preserving details than the filter in Photoshop software and other filters.
ER -