An effective alternating direction method of multipliers for color image restoration
Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color imag...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zhang, Jianjun [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021transfer abstract |
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| Schlagwörter: |
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| Umfang: |
14 |
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| Übergeordnetes Werk: |
Enthalten in: Impact of rogue active regions on hemispheric asymmetry - Nagy, Melinda ELSEVIER, 2018, transactions of IMACS, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:164 ; year:2021 ; pages:43-56 ; extent:14 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.apnum.2020.07.008 |
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ELV052932478 |
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| 520 | |a Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. | ||
| 520 | |a Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. | ||
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10.1016/j.apnum.2020.07.008 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001285.pica (DE-627)ELV052932478 (ELSEVIER)S0168-9274(20)30208-7 DE-627 ger DE-627 rakwb eng 520 620 VZ 39.00 bkl 50.93 bkl Zhang, Jianjun verfasserin aut An effective alternating direction method of multipliers for color image restoration 2021transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. Ill-posed problems Elsevier Gaussian noise Elsevier Total variation Elsevier Image restoration Elsevier Regularization Elsevier Matrix equation Elsevier Nagy, James G. oth Enthalten in Elsevier Nagy, Melinda ELSEVIER Impact of rogue active regions on hemispheric asymmetry 2018 transactions of IMACS Amsterdam [u.a.] (DE-627)ELV001550608 volume:164 year:2021 pages:43-56 extent:14 https://doi.org/10.1016/j.apnum.2020.07.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-AST 39.00 Astronomie: Allgemeines VZ 50.93 Weltraumforschung VZ AR 164 2021 43-56 14 |
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10.1016/j.apnum.2020.07.008 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001285.pica (DE-627)ELV052932478 (ELSEVIER)S0168-9274(20)30208-7 DE-627 ger DE-627 rakwb eng 520 620 VZ 39.00 bkl 50.93 bkl Zhang, Jianjun verfasserin aut An effective alternating direction method of multipliers for color image restoration 2021transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. Ill-posed problems Elsevier Gaussian noise Elsevier Total variation Elsevier Image restoration Elsevier Regularization Elsevier Matrix equation Elsevier Nagy, James G. oth Enthalten in Elsevier Nagy, Melinda ELSEVIER Impact of rogue active regions on hemispheric asymmetry 2018 transactions of IMACS Amsterdam [u.a.] (DE-627)ELV001550608 volume:164 year:2021 pages:43-56 extent:14 https://doi.org/10.1016/j.apnum.2020.07.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-AST 39.00 Astronomie: Allgemeines VZ 50.93 Weltraumforschung VZ AR 164 2021 43-56 14 |
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10.1016/j.apnum.2020.07.008 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001285.pica (DE-627)ELV052932478 (ELSEVIER)S0168-9274(20)30208-7 DE-627 ger DE-627 rakwb eng 520 620 VZ 39.00 bkl 50.93 bkl Zhang, Jianjun verfasserin aut An effective alternating direction method of multipliers for color image restoration 2021transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. Ill-posed problems Elsevier Gaussian noise Elsevier Total variation Elsevier Image restoration Elsevier Regularization Elsevier Matrix equation Elsevier Nagy, James G. oth Enthalten in Elsevier Nagy, Melinda ELSEVIER Impact of rogue active regions on hemispheric asymmetry 2018 transactions of IMACS Amsterdam [u.a.] (DE-627)ELV001550608 volume:164 year:2021 pages:43-56 extent:14 https://doi.org/10.1016/j.apnum.2020.07.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-AST 39.00 Astronomie: Allgemeines VZ 50.93 Weltraumforschung VZ AR 164 2021 43-56 14 |
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10.1016/j.apnum.2020.07.008 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001285.pica (DE-627)ELV052932478 (ELSEVIER)S0168-9274(20)30208-7 DE-627 ger DE-627 rakwb eng 520 620 VZ 39.00 bkl 50.93 bkl Zhang, Jianjun verfasserin aut An effective alternating direction method of multipliers for color image restoration 2021transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. Ill-posed problems Elsevier Gaussian noise Elsevier Total variation Elsevier Image restoration Elsevier Regularization Elsevier Matrix equation Elsevier Nagy, James G. oth Enthalten in Elsevier Nagy, Melinda ELSEVIER Impact of rogue active regions on hemispheric asymmetry 2018 transactions of IMACS Amsterdam [u.a.] (DE-627)ELV001550608 volume:164 year:2021 pages:43-56 extent:14 https://doi.org/10.1016/j.apnum.2020.07.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-AST 39.00 Astronomie: Allgemeines VZ 50.93 Weltraumforschung VZ AR 164 2021 43-56 14 |
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10.1016/j.apnum.2020.07.008 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001285.pica (DE-627)ELV052932478 (ELSEVIER)S0168-9274(20)30208-7 DE-627 ger DE-627 rakwb eng 520 620 VZ 39.00 bkl 50.93 bkl Zhang, Jianjun verfasserin aut An effective alternating direction method of multipliers for color image restoration 2021transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. Ill-posed problems Elsevier Gaussian noise Elsevier Total variation Elsevier Image restoration Elsevier Regularization Elsevier Matrix equation Elsevier Nagy, James G. oth Enthalten in Elsevier Nagy, Melinda ELSEVIER Impact of rogue active regions on hemispheric asymmetry 2018 transactions of IMACS Amsterdam [u.a.] (DE-627)ELV001550608 volume:164 year:2021 pages:43-56 extent:14 https://doi.org/10.1016/j.apnum.2020.07.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-AST 39.00 Astronomie: Allgemeines VZ 50.93 Weltraumforschung VZ AR 164 2021 43-56 14 |
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| title_full |
An effective alternating direction method of multipliers for color image restoration |
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Zhang, Jianjun |
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Impact of rogue active regions on hemispheric asymmetry |
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Impact of rogue active regions on hemispheric asymmetry |
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eng |
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2021 |
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Zhang, Jianjun |
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Elektronische Aufsätze |
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Zhang, Jianjun |
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10.1016/j.apnum.2020.07.008 |
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520 620 |
| title_sort |
an effective alternating direction method of multipliers for color image restoration |
| title_auth |
An effective alternating direction method of multipliers for color image restoration |
| abstract |
Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. |
| abstractGer |
Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. |
| abstract_unstemmed |
Color image restoration is an ill-posed problem, and regularization is necessary. In this paper, we first formulate the color image restoration problem into a constrained minimization problem that minimizes a quadratic functional and subject to a constraint that the total variation of the color image is less than a given parameter δ. The advantages of the constrained minimization problem over the traditional unconstrained one is that the parameter δ has an obvious physical meaning and is easy to select. However solving the constrained minimization problem is generally more difficult than solving the corresponding unconstrained form. We propose an effective alternating direction method of multipliers for color image restoration by using the structure of the problem. We prove the convergence of the method in detail. Experimental results demonstrate that the proposed method is feasible and much more effective for color image restoration. |
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GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-AST |
| title_short |
An effective alternating direction method of multipliers for color image restoration |
| url |
https://doi.org/10.1016/j.apnum.2020.07.008 |
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true |
| author2 |
Nagy, James G. |
| author2Str |
Nagy, James G. |
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10.1016/j.apnum.2020.07.008 |
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2024-07-06T17:33:21.998Z |
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