Video Noise Reduction Method Using Adaptive Spatial-Temporal Filtering
We proposed a novel method of video noise reduction based on the spatial Wiener filter and the temporal filter. In the proposed spatial Wiener filter, both the amount of noise and the size of the mask are taken into consideration. The proposed model has a great capacity to be adaptive in each area i...
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Format: | Article |
Language: | English |
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Wiley
2015-01-01
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Series: | Discrete Dynamics in Nature and Society |
Online Access: | http://dx.doi.org/10.1155/2015/351763 |
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author | Ali Abdullah Yahya Jieqing Tan Lian Li |
author_facet | Ali Abdullah Yahya Jieqing Tan Lian Li |
author_sort | Ali Abdullah Yahya |
collection | DOAJ |
description | We proposed a novel method of video noise reduction based on the spatial Wiener filter and the temporal filter. In the proposed spatial Wiener filter, both the amount of noise and the size of the mask are taken into consideration. The proposed model has a great capacity to be adaptive in each area in accordance with the amount of noise. In the proposed model, the motion detector is applied to control the noise removal process in accordance with the area’s information (i.e., static or movable). More accurately, more noise removal is done in the areas that are potentially still areas and less removal in the areas that are potentially motion areas. The proposed model achieves a maximum gain of 7.6 dB and capacity of conserving the significant image features (e.g., edges). The experimental results demonstrate that the new approach is more efficient than reference methods in terms of noise removal and edges preservation. |
format | Article |
id | doaj-art-7741ddbff47e4c9cb185ee4d96212fc8 |
institution | Kabale University |
issn | 1026-0226 1607-887X |
language | English |
publishDate | 2015-01-01 |
publisher | Wiley |
record_format | Article |
series | Discrete Dynamics in Nature and Society |
spelling | doaj-art-7741ddbff47e4c9cb185ee4d96212fc82025-02-03T01:21:58ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2015-01-01201510.1155/2015/351763351763Video Noise Reduction Method Using Adaptive Spatial-Temporal FilteringAli Abdullah Yahya0Jieqing Tan1Lian Li2 School of Computer and Information, Hefei University of Technology, Hefei 230009, China School of Computer and Information, Hefei University of Technology, Hefei 230009, China School of Computer and Information, Hefei University of Technology, Hefei 230009, ChinaWe proposed a novel method of video noise reduction based on the spatial Wiener filter and the temporal filter. In the proposed spatial Wiener filter, both the amount of noise and the size of the mask are taken into consideration. The proposed model has a great capacity to be adaptive in each area in accordance with the amount of noise. In the proposed model, the motion detector is applied to control the noise removal process in accordance with the area’s information (i.e., static or movable). More accurately, more noise removal is done in the areas that are potentially still areas and less removal in the areas that are potentially motion areas. The proposed model achieves a maximum gain of 7.6 dB and capacity of conserving the significant image features (e.g., edges). The experimental results demonstrate that the new approach is more efficient than reference methods in terms of noise removal and edges preservation.http://dx.doi.org/10.1155/2015/351763 |
spellingShingle | Ali Abdullah Yahya Jieqing Tan Lian Li Video Noise Reduction Method Using Adaptive Spatial-Temporal Filtering Discrete Dynamics in Nature and Society |
title | Video Noise Reduction Method Using Adaptive Spatial-Temporal Filtering |
title_full | Video Noise Reduction Method Using Adaptive Spatial-Temporal Filtering |
title_fullStr | Video Noise Reduction Method Using Adaptive Spatial-Temporal Filtering |
title_full_unstemmed | Video Noise Reduction Method Using Adaptive Spatial-Temporal Filtering |
title_short | Video Noise Reduction Method Using Adaptive Spatial-Temporal Filtering |
title_sort | video noise reduction method using adaptive spatial temporal filtering |
url | http://dx.doi.org/10.1155/2015/351763 |
work_keys_str_mv | AT aliabdullahyahya videonoisereductionmethodusingadaptivespatialtemporalfiltering AT jieqingtan videonoisereductionmethodusingadaptivespatialtemporalfiltering AT lianli videonoisereductionmethodusingadaptivespatialtemporalfiltering |