Union Laplacian pyramid with multiple features for medical image fusion
The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Du, Jiao [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016transfer abstract |
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| Schlagwörter: |
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| Umfang: |
14 |
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| Übergeordnetes Werk: |
Enthalten in: The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast - Liu, Yang ELSEVIER, 2018, an international journal, Amsterdam |
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| Übergeordnetes Werk: |
volume:194 ; year:2016 ; day:19 ; month:06 ; pages:326-339 ; extent:14 |
| Links: |
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| DOI / URN: |
10.1016/j.neucom.2016.02.047 |
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| 245 | 1 | 0 | |a Union Laplacian pyramid with multiple features for medical image fusion |
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| 520 | |a The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. | ||
| 520 | |a The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. | ||
| 650 | 7 | |a Pyramid |2 Elsevier | |
| 650 | 7 | |a Multiple features |2 Elsevier | |
| 650 | 7 | |a Outline enhancement |2 Elsevier | |
| 650 | 7 | |a Contrast enhancement |2 Elsevier | |
| 650 | 7 | |a Objective image quality metrics |2 Elsevier | |
| 650 | 7 | |a Image fusion |2 Elsevier | |
| 700 | 1 | |a Li, Weisheng |4 oth | |
| 700 | 1 | |a Xiao, Bin |4 oth | |
| 700 | 1 | |a Nawaz, Qamar |4 oth | |
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10.1016/j.neucom.2016.02.047 doi GBV00000000000207A.pica (DE-627)ELV024598577 (ELSEVIER)S0925-2312(16)00294-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Du, Jiao verfasserin aut Union Laplacian pyramid with multiple features for medical image fusion 2016transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. Pyramid Elsevier Multiple features Elsevier Outline enhancement Elsevier Contrast enhancement Elsevier Objective image quality metrics Elsevier Image fusion Elsevier Li, Weisheng oth Xiao, Bin oth Nawaz, Qamar oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:194 year:2016 day:19 month:06 pages:326-339 extent:14 https://doi.org/10.1016/j.neucom.2016.02.047 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 194 2016 19 0619 326-339 14 045F 610 |
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10.1016/j.neucom.2016.02.047 doi GBV00000000000207A.pica (DE-627)ELV024598577 (ELSEVIER)S0925-2312(16)00294-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Du, Jiao verfasserin aut Union Laplacian pyramid with multiple features for medical image fusion 2016transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. Pyramid Elsevier Multiple features Elsevier Outline enhancement Elsevier Contrast enhancement Elsevier Objective image quality metrics Elsevier Image fusion Elsevier Li, Weisheng oth Xiao, Bin oth Nawaz, Qamar oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:194 year:2016 day:19 month:06 pages:326-339 extent:14 https://doi.org/10.1016/j.neucom.2016.02.047 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 194 2016 19 0619 326-339 14 045F 610 |
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10.1016/j.neucom.2016.02.047 doi GBV00000000000207A.pica (DE-627)ELV024598577 (ELSEVIER)S0925-2312(16)00294-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Du, Jiao verfasserin aut Union Laplacian pyramid with multiple features for medical image fusion 2016transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. Pyramid Elsevier Multiple features Elsevier Outline enhancement Elsevier Contrast enhancement Elsevier Objective image quality metrics Elsevier Image fusion Elsevier Li, Weisheng oth Xiao, Bin oth Nawaz, Qamar oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:194 year:2016 day:19 month:06 pages:326-339 extent:14 https://doi.org/10.1016/j.neucom.2016.02.047 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 194 2016 19 0619 326-339 14 045F 610 |
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10.1016/j.neucom.2016.02.047 doi GBV00000000000207A.pica (DE-627)ELV024598577 (ELSEVIER)S0925-2312(16)00294-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Du, Jiao verfasserin aut Union Laplacian pyramid with multiple features for medical image fusion 2016transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. Pyramid Elsevier Multiple features Elsevier Outline enhancement Elsevier Contrast enhancement Elsevier Objective image quality metrics Elsevier Image fusion Elsevier Li, Weisheng oth Xiao, Bin oth Nawaz, Qamar oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:194 year:2016 day:19 month:06 pages:326-339 extent:14 https://doi.org/10.1016/j.neucom.2016.02.047 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 194 2016 19 0619 326-339 14 045F 610 |
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10.1016/j.neucom.2016.02.047 doi GBV00000000000207A.pica (DE-627)ELV024598577 (ELSEVIER)S0925-2312(16)00294-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Du, Jiao verfasserin aut Union Laplacian pyramid with multiple features for medical image fusion 2016transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. Pyramid Elsevier Multiple features Elsevier Outline enhancement Elsevier Contrast enhancement Elsevier Objective image quality metrics Elsevier Image fusion Elsevier Li, Weisheng oth Xiao, Bin oth Nawaz, Qamar oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:194 year:2016 day:19 month:06 pages:326-339 extent:14 https://doi.org/10.1016/j.neucom.2016.02.047 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 194 2016 19 0619 326-339 14 045F 610 |
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Enthalten in The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast Amsterdam volume:194 year:2016 day:19 month:06 pages:326-339 extent:14 |
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Enthalten in The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast Amsterdam volume:194 year:2016 day:19 month:06 pages:326-339 extent:14 |
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The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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Du, Jiao @@aut@@ Li, Weisheng @@oth@@ Xiao, Bin @@oth@@ Nawaz, Qamar @@oth@@ |
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The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. |
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The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. |
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The Laplacian pyramid has been widely used for decomposing images into multiple scales. However, the Laplacian pyramid is believed as being unable to represent outline and contrast of the images well. To tackle these tasks, an approach union Laplacian pyramid with multiple features is presented for accurately transferring salient features from the input medical images into a single fused image. Firstly, the input images are transformed into their multi-scale representations by Laplacian pyramid. Secondly, the contrast feature map and outline feature map are extracted from the images at each scale, respectively. Thirdly, after extracting the multiple features, an efficient fusion scheme is developed to combine the pyramid coefficients. Lastly, the fused image is obtained by a reconstruction process of the inversed pyramid. Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics. The contrast is also well preserved by histogram analysis of images. |
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