Specular reflection removal of ocean surface remote sensing images from UAVs
Abstract Images captured by UAVs above the sea surface often contain lots of highlight regions due to the specular reflection of solar radiation on the non-flat sea surface. The existence of a great deal of specular highlight components may cover the objects under the water which is negative to thos...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wang, Shengke [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: Multimedia tools and applications - Springer US, 1995, 77(2018), 9 vom: 08. Feb., Seite 11363-11379 |
|---|---|
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volume:77 ; year:2018 ; number:9 ; day:08 ; month:02 ; pages:11363-11379 |
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10.1007/s11042-017-5551-7 |
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| 520 | |a Abstract Images captured by UAVs above the sea surface often contain lots of highlight regions due to the specular reflection of solar radiation on the non-flat sea surface. The existence of a great deal of specular highlight components may cover the objects under the water which is negative to those applications based on the UAV remote sensing images. In this paper, we present a method to remove the specular reflection on the RGB images of ocean surface. The intensity of specular highlight components is much larger than that of diffuse components in the images, simply subtracting the highlight component form the original image will leave a lot of holes. So our method contains two main steps: highlight regions detection and restoration of those regions. We use the method based on the intensity ratio to extract the regions affected by the specular reflection. Then we use the local information around those highlight regions to restore the intensity of those pixels. The experimental results indicate that the proposed method can effectively remove the specular reflection and keep details of ocean surface images. | ||
| 650 | 4 | |a UAVs | |
| 650 | 4 | |a Remote sensing | |
| 650 | 4 | |a Specular reflection | |
| 650 | 4 | |a Ocean surface | |
| 700 | 1 | |a Yu, Changyin |4 aut | |
| 700 | 1 | |a Sun, Yujuan |4 aut | |
| 700 | 1 | |a Gao, Feng |4 aut | |
| 700 | 1 | |a Dong, Junyu |4 aut | |
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10.1007/s11042-017-5551-7 doi (DE-627)OLC2035047064 (DE-He213)s11042-017-5551-7-p DE-627 ger DE-627 rakwb eng 070 004 VZ Wang, Shengke verfasserin (orcid)0000-0002-4906-8773 aut Specular reflection removal of ocean surface remote sensing images from UAVs 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Images captured by UAVs above the sea surface often contain lots of highlight regions due to the specular reflection of solar radiation on the non-flat sea surface. The existence of a great deal of specular highlight components may cover the objects under the water which is negative to those applications based on the UAV remote sensing images. In this paper, we present a method to remove the specular reflection on the RGB images of ocean surface. The intensity of specular highlight components is much larger than that of diffuse components in the images, simply subtracting the highlight component form the original image will leave a lot of holes. So our method contains two main steps: highlight regions detection and restoration of those regions. We use the method based on the intensity ratio to extract the regions affected by the specular reflection. Then we use the local information around those highlight regions to restore the intensity of those pixels. The experimental results indicate that the proposed method can effectively remove the specular reflection and keep details of ocean surface images. UAVs Remote sensing Specular reflection Ocean surface Yu, Changyin aut Sun, Yujuan aut Gao, Feng aut Dong, Junyu aut Enthalten in Multimedia tools and applications Springer US, 1995 77(2018), 9 vom: 08. Feb., Seite 11363-11379 (DE-627)189064145 (DE-600)1287642-2 (DE-576)052842126 1380-7501 nnns volume:77 year:2018 number:9 day:08 month:02 pages:11363-11379 https://doi.org/10.1007/s11042-017-5551-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-BUB SSG-OLC-MKW GBV_ILN_70 AR 77 2018 9 08 02 11363-11379 |
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10.1007/s11042-017-5551-7 doi (DE-627)OLC2035047064 (DE-He213)s11042-017-5551-7-p DE-627 ger DE-627 rakwb eng 070 004 VZ Wang, Shengke verfasserin (orcid)0000-0002-4906-8773 aut Specular reflection removal of ocean surface remote sensing images from UAVs 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Images captured by UAVs above the sea surface often contain lots of highlight regions due to the specular reflection of solar radiation on the non-flat sea surface. The existence of a great deal of specular highlight components may cover the objects under the water which is negative to those applications based on the UAV remote sensing images. In this paper, we present a method to remove the specular reflection on the RGB images of ocean surface. The intensity of specular highlight components is much larger than that of diffuse components in the images, simply subtracting the highlight component form the original image will leave a lot of holes. So our method contains two main steps: highlight regions detection and restoration of those regions. We use the method based on the intensity ratio to extract the regions affected by the specular reflection. Then we use the local information around those highlight regions to restore the intensity of those pixels. The experimental results indicate that the proposed method can effectively remove the specular reflection and keep details of ocean surface images. UAVs Remote sensing Specular reflection Ocean surface Yu, Changyin aut Sun, Yujuan aut Gao, Feng aut Dong, Junyu aut Enthalten in Multimedia tools and applications Springer US, 1995 77(2018), 9 vom: 08. Feb., Seite 11363-11379 (DE-627)189064145 (DE-600)1287642-2 (DE-576)052842126 1380-7501 nnns volume:77 year:2018 number:9 day:08 month:02 pages:11363-11379 https://doi.org/10.1007/s11042-017-5551-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-BUB SSG-OLC-MKW GBV_ILN_70 AR 77 2018 9 08 02 11363-11379 |
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10.1007/s11042-017-5551-7 doi (DE-627)OLC2035047064 (DE-He213)s11042-017-5551-7-p DE-627 ger DE-627 rakwb eng 070 004 VZ Wang, Shengke verfasserin (orcid)0000-0002-4906-8773 aut Specular reflection removal of ocean surface remote sensing images from UAVs 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Images captured by UAVs above the sea surface often contain lots of highlight regions due to the specular reflection of solar radiation on the non-flat sea surface. The existence of a great deal of specular highlight components may cover the objects under the water which is negative to those applications based on the UAV remote sensing images. In this paper, we present a method to remove the specular reflection on the RGB images of ocean surface. The intensity of specular highlight components is much larger than that of diffuse components in the images, simply subtracting the highlight component form the original image will leave a lot of holes. So our method contains two main steps: highlight regions detection and restoration of those regions. We use the method based on the intensity ratio to extract the regions affected by the specular reflection. Then we use the local information around those highlight regions to restore the intensity of those pixels. The experimental results indicate that the proposed method can effectively remove the specular reflection and keep details of ocean surface images. UAVs Remote sensing Specular reflection Ocean surface Yu, Changyin aut Sun, Yujuan aut Gao, Feng aut Dong, Junyu aut Enthalten in Multimedia tools and applications Springer US, 1995 77(2018), 9 vom: 08. Feb., Seite 11363-11379 (DE-627)189064145 (DE-600)1287642-2 (DE-576)052842126 1380-7501 nnns volume:77 year:2018 number:9 day:08 month:02 pages:11363-11379 https://doi.org/10.1007/s11042-017-5551-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-BUB SSG-OLC-MKW GBV_ILN_70 AR 77 2018 9 08 02 11363-11379 |
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10.1007/s11042-017-5551-7 doi (DE-627)OLC2035047064 (DE-He213)s11042-017-5551-7-p DE-627 ger DE-627 rakwb eng 070 004 VZ Wang, Shengke verfasserin (orcid)0000-0002-4906-8773 aut Specular reflection removal of ocean surface remote sensing images from UAVs 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Images captured by UAVs above the sea surface often contain lots of highlight regions due to the specular reflection of solar radiation on the non-flat sea surface. The existence of a great deal of specular highlight components may cover the objects under the water which is negative to those applications based on the UAV remote sensing images. In this paper, we present a method to remove the specular reflection on the RGB images of ocean surface. The intensity of specular highlight components is much larger than that of diffuse components in the images, simply subtracting the highlight component form the original image will leave a lot of holes. So our method contains two main steps: highlight regions detection and restoration of those regions. We use the method based on the intensity ratio to extract the regions affected by the specular reflection. Then we use the local information around those highlight regions to restore the intensity of those pixels. The experimental results indicate that the proposed method can effectively remove the specular reflection and keep details of ocean surface images. UAVs Remote sensing Specular reflection Ocean surface Yu, Changyin aut Sun, Yujuan aut Gao, Feng aut Dong, Junyu aut Enthalten in Multimedia tools and applications Springer US, 1995 77(2018), 9 vom: 08. Feb., Seite 11363-11379 (DE-627)189064145 (DE-600)1287642-2 (DE-576)052842126 1380-7501 nnns volume:77 year:2018 number:9 day:08 month:02 pages:11363-11379 https://doi.org/10.1007/s11042-017-5551-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-BUB SSG-OLC-MKW GBV_ILN_70 AR 77 2018 9 08 02 11363-11379 |
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Abstract Images captured by UAVs above the sea surface often contain lots of highlight regions due to the specular reflection of solar radiation on the non-flat sea surface. The existence of a great deal of specular highlight components may cover the objects under the water which is negative to those applications based on the UAV remote sensing images. In this paper, we present a method to remove the specular reflection on the RGB images of ocean surface. The intensity of specular highlight components is much larger than that of diffuse components in the images, simply subtracting the highlight component form the original image will leave a lot of holes. So our method contains two main steps: highlight regions detection and restoration of those regions. We use the method based on the intensity ratio to extract the regions affected by the specular reflection. Then we use the local information around those highlight regions to restore the intensity of those pixels. The experimental results indicate that the proposed method can effectively remove the specular reflection and keep details of ocean surface images. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
| abstractGer |
Abstract Images captured by UAVs above the sea surface often contain lots of highlight regions due to the specular reflection of solar radiation on the non-flat sea surface. The existence of a great deal of specular highlight components may cover the objects under the water which is negative to those applications based on the UAV remote sensing images. In this paper, we present a method to remove the specular reflection on the RGB images of ocean surface. The intensity of specular highlight components is much larger than that of diffuse components in the images, simply subtracting the highlight component form the original image will leave a lot of holes. So our method contains two main steps: highlight regions detection and restoration of those regions. We use the method based on the intensity ratio to extract the regions affected by the specular reflection. Then we use the local information around those highlight regions to restore the intensity of those pixels. The experimental results indicate that the proposed method can effectively remove the specular reflection and keep details of ocean surface images. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
| abstract_unstemmed |
Abstract Images captured by UAVs above the sea surface often contain lots of highlight regions due to the specular reflection of solar radiation on the non-flat sea surface. The existence of a great deal of specular highlight components may cover the objects under the water which is negative to those applications based on the UAV remote sensing images. In this paper, we present a method to remove the specular reflection on the RGB images of ocean surface. The intensity of specular highlight components is much larger than that of diffuse components in the images, simply subtracting the highlight component form the original image will leave a lot of holes. So our method contains two main steps: highlight regions detection and restoration of those regions. We use the method based on the intensity ratio to extract the regions affected by the specular reflection. Then we use the local information around those highlight regions to restore the intensity of those pixels. The experimental results indicate that the proposed method can effectively remove the specular reflection and keep details of ocean surface images. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
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| title_short |
Specular reflection removal of ocean surface remote sensing images from UAVs |
| url |
https://doi.org/10.1007/s11042-017-5551-7 |
| remote_bool |
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| author2 |
Yu, Changyin Sun, Yujuan Gao, Feng Dong, Junyu |
| author2Str |
Yu, Changyin Sun, Yujuan Gao, Feng Dong, Junyu |
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| doi_str |
10.1007/s11042-017-5551-7 |
| up_date |
2024-07-03T23:35:18.303Z |
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