IBM3D: Integer BM3D for Efficient Image Denoising
Abstract The block-matching collaborative filtering (BM3D) denoiser has been considered as a strong performer in image denoising, but it has high computational cost in block-matching and 3D transforms, which limits its practical applications, particularly in embedded video processing systems. In thi...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Yang, Jingyu [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2018 |
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| Übergeordnetes Werk: |
Enthalten in: Circuits, systems and signal processing - Springer US, 1982, 38(2018), 2 vom: 18. Juni, Seite 750-763 |
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| Übergeordnetes Werk: |
volume:38 ; year:2018 ; number:2 ; day:18 ; month:06 ; pages:750-763 |
| Links: |
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| DOI / URN: |
10.1007/s00034-018-0882-9 |
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| 520 | |a Abstract The block-matching collaborative filtering (BM3D) denoiser has been considered as a strong performer in image denoising, but it has high computational cost in block-matching and 3D transforms, which limits its practical applications, particularly in embedded video processing systems. In this paper, we propose an integer BM3D (IBM3D) that involves only integer operations. To integerize 3D transforms, the balance of approximation accuracy and denoising performance is carefully investigated for a wide range of noise levels. We propose an integer Wiener filter and investigate its performance over the original empirical Wiener filter with both analytical analysis and experimental verifications. The Kaiser window weighting is also integerized. The experiment results show that the proposed IBM3D provides comparable denoising performance to the original BM3D, and generates even better results for high noise levels. The proposed IBM3D requires less computation than the original BM3D, and can be deployed into embedded systems without or with limited floating-point computation resources, and ported to chips with smaller circuit areas and less power consumption. | ||
| 650 | 4 | |a Image denoising | |
| 650 | 4 | |a Integer implementation | |
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| 700 | 1 | |a Zhang, Xue |4 aut | |
| 700 | 1 | |a Yue, Huanjing |0 (orcid)0000-0001-6852-2639 |4 aut | |
| 700 | 1 | |a Cai, Changrui |4 aut | |
| 700 | 1 | |a Hou, Chunping |4 aut | |
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10.1007/s00034-018-0882-9 doi (DE-627)OLC2034853962 (DE-He213)s00034-018-0882-9-p DE-627 ger DE-627 rakwb eng 600 VZ Yang, Jingyu verfasserin aut IBM3D: Integer BM3D for Efficient Image Denoising 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract The block-matching collaborative filtering (BM3D) denoiser has been considered as a strong performer in image denoising, but it has high computational cost in block-matching and 3D transforms, which limits its practical applications, particularly in embedded video processing systems. In this paper, we propose an integer BM3D (IBM3D) that involves only integer operations. To integerize 3D transforms, the balance of approximation accuracy and denoising performance is carefully investigated for a wide range of noise levels. We propose an integer Wiener filter and investigate its performance over the original empirical Wiener filter with both analytical analysis and experimental verifications. The Kaiser window weighting is also integerized. The experiment results show that the proposed IBM3D provides comparable denoising performance to the original BM3D, and generates even better results for high noise levels. The proposed IBM3D requires less computation than the original BM3D, and can be deployed into embedded systems without or with limited floating-point computation resources, and ported to chips with smaller circuit areas and less power consumption. Image denoising Integer implementation DWT DCT Wiener filtering Zhang, Xue aut Yue, Huanjing (orcid)0000-0001-6852-2639 aut Cai, Changrui aut Hou, Chunping aut Enthalten in Circuits, systems and signal processing Springer US, 1982 38(2018), 2 vom: 18. Juni, Seite 750-763 (DE-627)130312134 (DE-600)588684-3 (DE-576)015889939 0278-081X nnns volume:38 year:2018 number:2 day:18 month:06 pages:750-763 https://doi.org/10.1007/s00034-018-0882-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2244 AR 38 2018 2 18 06 750-763 |
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10.1007/s00034-018-0882-9 doi (DE-627)OLC2034853962 (DE-He213)s00034-018-0882-9-p DE-627 ger DE-627 rakwb eng 600 VZ Yang, Jingyu verfasserin aut IBM3D: Integer BM3D for Efficient Image Denoising 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract The block-matching collaborative filtering (BM3D) denoiser has been considered as a strong performer in image denoising, but it has high computational cost in block-matching and 3D transforms, which limits its practical applications, particularly in embedded video processing systems. In this paper, we propose an integer BM3D (IBM3D) that involves only integer operations. To integerize 3D transforms, the balance of approximation accuracy and denoising performance is carefully investigated for a wide range of noise levels. We propose an integer Wiener filter and investigate its performance over the original empirical Wiener filter with both analytical analysis and experimental verifications. The Kaiser window weighting is also integerized. The experiment results show that the proposed IBM3D provides comparable denoising performance to the original BM3D, and generates even better results for high noise levels. The proposed IBM3D requires less computation than the original BM3D, and can be deployed into embedded systems without or with limited floating-point computation resources, and ported to chips with smaller circuit areas and less power consumption. Image denoising Integer implementation DWT DCT Wiener filtering Zhang, Xue aut Yue, Huanjing (orcid)0000-0001-6852-2639 aut Cai, Changrui aut Hou, Chunping aut Enthalten in Circuits, systems and signal processing Springer US, 1982 38(2018), 2 vom: 18. Juni, Seite 750-763 (DE-627)130312134 (DE-600)588684-3 (DE-576)015889939 0278-081X nnns volume:38 year:2018 number:2 day:18 month:06 pages:750-763 https://doi.org/10.1007/s00034-018-0882-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2244 AR 38 2018 2 18 06 750-763 |
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10.1007/s00034-018-0882-9 doi (DE-627)OLC2034853962 (DE-He213)s00034-018-0882-9-p DE-627 ger DE-627 rakwb eng 600 VZ Yang, Jingyu verfasserin aut IBM3D: Integer BM3D for Efficient Image Denoising 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract The block-matching collaborative filtering (BM3D) denoiser has been considered as a strong performer in image denoising, but it has high computational cost in block-matching and 3D transforms, which limits its practical applications, particularly in embedded video processing systems. In this paper, we propose an integer BM3D (IBM3D) that involves only integer operations. To integerize 3D transforms, the balance of approximation accuracy and denoising performance is carefully investigated for a wide range of noise levels. We propose an integer Wiener filter and investigate its performance over the original empirical Wiener filter with both analytical analysis and experimental verifications. The Kaiser window weighting is also integerized. The experiment results show that the proposed IBM3D provides comparable denoising performance to the original BM3D, and generates even better results for high noise levels. The proposed IBM3D requires less computation than the original BM3D, and can be deployed into embedded systems without or with limited floating-point computation resources, and ported to chips with smaller circuit areas and less power consumption. Image denoising Integer implementation DWT DCT Wiener filtering Zhang, Xue aut Yue, Huanjing (orcid)0000-0001-6852-2639 aut Cai, Changrui aut Hou, Chunping aut Enthalten in Circuits, systems and signal processing Springer US, 1982 38(2018), 2 vom: 18. Juni, Seite 750-763 (DE-627)130312134 (DE-600)588684-3 (DE-576)015889939 0278-081X nnns volume:38 year:2018 number:2 day:18 month:06 pages:750-763 https://doi.org/10.1007/s00034-018-0882-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2244 AR 38 2018 2 18 06 750-763 |
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10.1007/s00034-018-0882-9 doi (DE-627)OLC2034853962 (DE-He213)s00034-018-0882-9-p DE-627 ger DE-627 rakwb eng 600 VZ Yang, Jingyu verfasserin aut IBM3D: Integer BM3D for Efficient Image Denoising 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract The block-matching collaborative filtering (BM3D) denoiser has been considered as a strong performer in image denoising, but it has high computational cost in block-matching and 3D transforms, which limits its practical applications, particularly in embedded video processing systems. In this paper, we propose an integer BM3D (IBM3D) that involves only integer operations. To integerize 3D transforms, the balance of approximation accuracy and denoising performance is carefully investigated for a wide range of noise levels. We propose an integer Wiener filter and investigate its performance over the original empirical Wiener filter with both analytical analysis and experimental verifications. The Kaiser window weighting is also integerized. The experiment results show that the proposed IBM3D provides comparable denoising performance to the original BM3D, and generates even better results for high noise levels. The proposed IBM3D requires less computation than the original BM3D, and can be deployed into embedded systems without or with limited floating-point computation resources, and ported to chips with smaller circuit areas and less power consumption. Image denoising Integer implementation DWT DCT Wiener filtering Zhang, Xue aut Yue, Huanjing (orcid)0000-0001-6852-2639 aut Cai, Changrui aut Hou, Chunping aut Enthalten in Circuits, systems and signal processing Springer US, 1982 38(2018), 2 vom: 18. Juni, Seite 750-763 (DE-627)130312134 (DE-600)588684-3 (DE-576)015889939 0278-081X nnns volume:38 year:2018 number:2 day:18 month:06 pages:750-763 https://doi.org/10.1007/s00034-018-0882-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2244 AR 38 2018 2 18 06 750-763 |
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10.1007/s00034-018-0882-9 doi (DE-627)OLC2034853962 (DE-He213)s00034-018-0882-9-p DE-627 ger DE-627 rakwb eng 600 VZ Yang, Jingyu verfasserin aut IBM3D: Integer BM3D for Efficient Image Denoising 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract The block-matching collaborative filtering (BM3D) denoiser has been considered as a strong performer in image denoising, but it has high computational cost in block-matching and 3D transforms, which limits its practical applications, particularly in embedded video processing systems. In this paper, we propose an integer BM3D (IBM3D) that involves only integer operations. To integerize 3D transforms, the balance of approximation accuracy and denoising performance is carefully investigated for a wide range of noise levels. We propose an integer Wiener filter and investigate its performance over the original empirical Wiener filter with both analytical analysis and experimental verifications. The Kaiser window weighting is also integerized. The experiment results show that the proposed IBM3D provides comparable denoising performance to the original BM3D, and generates even better results for high noise levels. The proposed IBM3D requires less computation than the original BM3D, and can be deployed into embedded systems without or with limited floating-point computation resources, and ported to chips with smaller circuit areas and less power consumption. Image denoising Integer implementation DWT DCT Wiener filtering Zhang, Xue aut Yue, Huanjing (orcid)0000-0001-6852-2639 aut Cai, Changrui aut Hou, Chunping aut Enthalten in Circuits, systems and signal processing Springer US, 1982 38(2018), 2 vom: 18. Juni, Seite 750-763 (DE-627)130312134 (DE-600)588684-3 (DE-576)015889939 0278-081X nnns volume:38 year:2018 number:2 day:18 month:06 pages:750-763 https://doi.org/10.1007/s00034-018-0882-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2244 AR 38 2018 2 18 06 750-763 |
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Abstract The block-matching collaborative filtering (BM3D) denoiser has been considered as a strong performer in image denoising, but it has high computational cost in block-matching and 3D transforms, which limits its practical applications, particularly in embedded video processing systems. In this paper, we propose an integer BM3D (IBM3D) that involves only integer operations. To integerize 3D transforms, the balance of approximation accuracy and denoising performance is carefully investigated for a wide range of noise levels. We propose an integer Wiener filter and investigate its performance over the original empirical Wiener filter with both analytical analysis and experimental verifications. The Kaiser window weighting is also integerized. The experiment results show that the proposed IBM3D provides comparable denoising performance to the original BM3D, and generates even better results for high noise levels. The proposed IBM3D requires less computation than the original BM3D, and can be deployed into embedded systems without or with limited floating-point computation resources, and ported to chips with smaller circuit areas and less power consumption. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
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Abstract The block-matching collaborative filtering (BM3D) denoiser has been considered as a strong performer in image denoising, but it has high computational cost in block-matching and 3D transforms, which limits its practical applications, particularly in embedded video processing systems. In this paper, we propose an integer BM3D (IBM3D) that involves only integer operations. To integerize 3D transforms, the balance of approximation accuracy and denoising performance is carefully investigated for a wide range of noise levels. We propose an integer Wiener filter and investigate its performance over the original empirical Wiener filter with both analytical analysis and experimental verifications. The Kaiser window weighting is also integerized. The experiment results show that the proposed IBM3D provides comparable denoising performance to the original BM3D, and generates even better results for high noise levels. The proposed IBM3D requires less computation than the original BM3D, and can be deployed into embedded systems without or with limited floating-point computation resources, and ported to chips with smaller circuit areas and less power consumption. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
| abstract_unstemmed |
Abstract The block-matching collaborative filtering (BM3D) denoiser has been considered as a strong performer in image denoising, but it has high computational cost in block-matching and 3D transforms, which limits its practical applications, particularly in embedded video processing systems. In this paper, we propose an integer BM3D (IBM3D) that involves only integer operations. To integerize 3D transforms, the balance of approximation accuracy and denoising performance is carefully investigated for a wide range of noise levels. We propose an integer Wiener filter and investigate its performance over the original empirical Wiener filter with both analytical analysis and experimental verifications. The Kaiser window weighting is also integerized. The experiment results show that the proposed IBM3D provides comparable denoising performance to the original BM3D, and generates even better results for high noise levels. The proposed IBM3D requires less computation than the original BM3D, and can be deployed into embedded systems without or with limited floating-point computation resources, and ported to chips with smaller circuit areas and less power consumption. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
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IBM3D: Integer BM3D for Efficient Image Denoising |
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Zhang, Xue Yue, Huanjing Cai, Changrui Hou, Chunping |
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