Video Denoising Based on a Spatiotemporal Kalman-Bilateral Mixture Model
We propose a video denoising method based on a spatiotemporal Kalman-bilateral mixture model to reduce the noise in video sequences that are captured with low light. To take full advantage of the strong spatiotemporal correlations of neighboring frames, motion estimation is first performed on video...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/438147 |
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| _version_ | 1832549134980087808 |
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| author | Chenglin Zuo Yu Liu Xin Tan Wei Wang Maojun Zhang |
| author_facet | Chenglin Zuo Yu Liu Xin Tan Wei Wang Maojun Zhang |
| author_sort | Chenglin Zuo |
| collection | DOAJ |
| description | We propose a video denoising method based on a spatiotemporal Kalman-bilateral mixture model to reduce the noise in video sequences that are captured with low light. To take full advantage of the strong spatiotemporal correlations of neighboring frames, motion estimation is first performed on video frames consisting of previously denoised frames and the current noisy frame by using block-matching method. Then, current noisy frame is processed in temporal domain and spatial domain by using Kalman filter and bilateral filter, respectively. Finally, by weighting the denoised frames from Kalman filtering and bilateral filtering, we can obtain a satisfactory result. Experimental results show that the performance of our proposed method is competitive when compared with state-of-the-art video denoising algorithms based on both peak signal-to-noise-ratio and structural similarity evaluations. |
| format | Article |
| id | doaj-art-f7e01b91249548918e398d387d64aac7 |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-f7e01b91249548918e398d387d64aac72025-02-03T06:12:15ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/438147438147Video Denoising Based on a Spatiotemporal Kalman-Bilateral Mixture ModelChenglin Zuo0Yu Liu1Xin Tan2Wei Wang3Maojun Zhang4College of Information System and Management, National University of Defense Technology, Changsha, Hunan 410073, ChinaCollege of Information System and Management, National University of Defense Technology, Changsha, Hunan 410073, ChinaCollege of Information System and Management, National University of Defense Technology, Changsha, Hunan 410073, ChinaCollege of Information System and Management, National University of Defense Technology, Changsha, Hunan 410073, ChinaCollege of Information System and Management, National University of Defense Technology, Changsha, Hunan 410073, ChinaWe propose a video denoising method based on a spatiotemporal Kalman-bilateral mixture model to reduce the noise in video sequences that are captured with low light. To take full advantage of the strong spatiotemporal correlations of neighboring frames, motion estimation is first performed on video frames consisting of previously denoised frames and the current noisy frame by using block-matching method. Then, current noisy frame is processed in temporal domain and spatial domain by using Kalman filter and bilateral filter, respectively. Finally, by weighting the denoised frames from Kalman filtering and bilateral filtering, we can obtain a satisfactory result. Experimental results show that the performance of our proposed method is competitive when compared with state-of-the-art video denoising algorithms based on both peak signal-to-noise-ratio and structural similarity evaluations.http://dx.doi.org/10.1155/2013/438147 |
| spellingShingle | Chenglin Zuo Yu Liu Xin Tan Wei Wang Maojun Zhang Video Denoising Based on a Spatiotemporal Kalman-Bilateral Mixture Model The Scientific World Journal |
| title | Video Denoising Based on a Spatiotemporal Kalman-Bilateral Mixture Model |
| title_full | Video Denoising Based on a Spatiotemporal Kalman-Bilateral Mixture Model |
| title_fullStr | Video Denoising Based on a Spatiotemporal Kalman-Bilateral Mixture Model |
| title_full_unstemmed | Video Denoising Based on a Spatiotemporal Kalman-Bilateral Mixture Model |
| title_short | Video Denoising Based on a Spatiotemporal Kalman-Bilateral Mixture Model |
| title_sort | video denoising based on a spatiotemporal kalman bilateral mixture model |
| url | http://dx.doi.org/10.1155/2013/438147 |
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