IEICE TRANSACTIONS on Fundamentals
Spatially Adaptive Noise Removal Algorithm Using Local Statistics
Summary :
In this letter, we propose a spatially adaptive noise removal algorithm using local statistics. The proposed algorithm consists of two stages: noise detection and removal. In order to solve the trade-off between the effective noise suppression and the over-smoothness of the reconstructed image, local statistics such as local maximum and the local weighted activity is defined. With the local statistics, the noise detection function is defined and a modified Gaussian filter is used to suppress the detected noise components. The experimental results demonstrate the effectiveness of the proposed algorithm.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E94-A No.1 pp.452-456
- Publication Date
- 2011/01/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E94.A.452
- Type of Manuscript
- LETTER
- Category
- Image
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Tuan-Anh NGUYEN, Won-Seon SONG, Min-Cheol HONG, "Spatially Adaptive Noise Removal Algorithm Using Local Statistics" in IEICE TRANSACTIONS on Fundamentals,
vol. E94-A, no. 1, pp. 452-456, January 2011, doi: 10.1587/transfun.E94.A.452.
Abstract: In this letter, we propose a spatially adaptive noise removal algorithm using local statistics. The proposed algorithm consists of two stages: noise detection and removal. In order to solve the trade-off between the effective noise suppression and the over-smoothness of the reconstructed image, local statistics such as local maximum and the local weighted activity is defined. With the local statistics, the noise detection function is defined and a modified Gaussian filter is used to suppress the detected noise components. The experimental results demonstrate the effectiveness of the proposed algorithm.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E94.A.452/_p
Copy
@ARTICLE{e94-a_1_452,
author={Tuan-Anh NGUYEN, Won-Seon SONG, Min-Cheol HONG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Spatially Adaptive Noise Removal Algorithm Using Local Statistics},
year={2011},
volume={E94-A},
number={1},
pages={452-456},
abstract={In this letter, we propose a spatially adaptive noise removal algorithm using local statistics. The proposed algorithm consists of two stages: noise detection and removal. In order to solve the trade-off between the effective noise suppression and the over-smoothness of the reconstructed image, local statistics such as local maximum and the local weighted activity is defined. With the local statistics, the noise detection function is defined and a modified Gaussian filter is used to suppress the detected noise components. The experimental results demonstrate the effectiveness of the proposed algorithm.},
keywords={},
doi={10.1587/transfun.E94.A.452},
ISSN={1745-1337},
month={January},}
Copy
TY - JOUR
TI - Spatially Adaptive Noise Removal Algorithm Using Local Statistics
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 452
EP - 456
AU - Tuan-Anh NGUYEN
AU - Won-Seon SONG
AU - Min-Cheol HONG
PY - 2011
DO - 10.1587/transfun.E94.A.452
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E94-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2011
AB - In this letter, we propose a spatially adaptive noise removal algorithm using local statistics. The proposed algorithm consists of two stages: noise detection and removal. In order to solve the trade-off between the effective noise suppression and the over-smoothness of the reconstructed image, local statistics such as local maximum and the local weighted activity is defined. With the local statistics, the noise detection function is defined and a modified Gaussian filter is used to suppress the detected noise components. The experimental results demonstrate the effectiveness of the proposed algorithm.
ER -
English
