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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dalam makalah ini, penapis kuasi-Gaussian, penapis kuasi-median dan penapis penyesuaian setempat diperkenalkan. Penapis vektor penyesuaian baharu berdasarkan anggaran hingar dicadangkan untuk menyekat hingar Gaussian dan/atau impuls. Untuk menganggarkan jenis dan tahap kerosakan hingar, pengesan hingar dan pengesan tepi diperkenalkan, dan dua parameter utama diperoleh untuk mencirikan hingar dalam imej warna. Selepas menganggar secara global jenis dan tahap kerosakan hingar, penapis penyesuaian setempat yang berbeza dipilih dengan betul untuk peningkatan imej. Semua imej bising, yang digunakan untuk menguji penapis dalam eksperimen, dihasilkan oleh perisian PaintShopPro dan Photoshop. Keputusan eksperimen menunjukkan bahawa penapis penyesuaian baharu berprestasi lebih baik dalam menyekat hingar dan mengekalkan butiran berbanding penapis dalam perisian Photoshop dan penapis lain.
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Salinan
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
Salinan
@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},}
Salinan
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 -