COLORIZING SENTINEL-1 SAR IMAGES USING A VARIATIONAL AUTOENCODER CONDITIONED ON SENTINEL-2 IMAGERY
In this paper, we have shown an approach for the automatic colorization of SAR backscatter images, which are usually provided in the form of single-channel gray-scale imagery. Using a deep generative model proposed for the purpose of photograph colorization and a Lab-space-based SAR-optical image fu...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2018-05-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2/1045/2018/isprs-archives-XLII-2-1045-2018.pdf |
| _version_ | 1818846878270226432 |
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| author | M. Schmitt L. H. Hughes M. Körner X. X. Zhu X. X. Zhu |
| author_facet | M. Schmitt L. H. Hughes M. Körner X. X. Zhu X. X. Zhu |
| author_sort | M. Schmitt |
| collection | DOAJ |
| description | In this paper, we have shown an approach for the automatic colorization of SAR backscatter images, which are usually provided in the form of single-channel gray-scale imagery. Using a deep generative model proposed for the purpose of photograph colorization and a Lab-space-based SAR-optical image fusion formulation, we are able to predict artificial color SAR images, which disclose much more information to the human interpreter than the original SAR data. Future work will aim at further adaption of the employed procedure to our special case of multi-sensor remote sensing imagery. Furthermore, we will investigate if the low-level representations learned intrinsically by the deep network can be used for SAR image interpretation in an end-to-end manner. |
| first_indexed | 2024-12-19T05:52:33Z |
| format | Article |
| id | doaj.art-76dd7f18a15744d68d27c23070866420 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-19T05:52:33Z |
| publishDate | 2018-05-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-76dd7f18a15744d68d27c230708664202022-12-21T20:33:33ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342018-05-01XLII-21045105110.5194/isprs-archives-XLII-2-1045-2018COLORIZING SENTINEL-1 SAR IMAGES USING A VARIATIONAL AUTOENCODER CONDITIONED ON SENTINEL-2 IMAGERYM. Schmitt0L. H. Hughes1M. Körner2X. X. Zhu3X. X. Zhu4Signal Processing in Earth Observation, Technical University of Munich (TUM), Munich, GermanySignal Processing in Earth Observation, Technical University of Munich (TUM), Munich, GermanyChair of Remote Sensing Technology, Technical University of Munich (TUM), Munich, GermanySignal Processing in Earth Observation, Technical University of Munich (TUM), Munich, GermanyRemote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Oberpfaffenhofen, GermanyIn this paper, we have shown an approach for the automatic colorization of SAR backscatter images, which are usually provided in the form of single-channel gray-scale imagery. Using a deep generative model proposed for the purpose of photograph colorization and a Lab-space-based SAR-optical image fusion formulation, we are able to predict artificial color SAR images, which disclose much more information to the human interpreter than the original SAR data. Future work will aim at further adaption of the employed procedure to our special case of multi-sensor remote sensing imagery. Furthermore, we will investigate if the low-level representations learned intrinsically by the deep network can be used for SAR image interpretation in an end-to-end manner.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2/1045/2018/isprs-archives-XLII-2-1045-2018.pdf |
| spellingShingle | M. Schmitt L. H. Hughes M. Körner X. X. Zhu X. X. Zhu COLORIZING SENTINEL-1 SAR IMAGES USING A VARIATIONAL AUTOENCODER CONDITIONED ON SENTINEL-2 IMAGERY The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | COLORIZING SENTINEL-1 SAR IMAGES USING A VARIATIONAL AUTOENCODER CONDITIONED ON SENTINEL-2 IMAGERY |
| title_full | COLORIZING SENTINEL-1 SAR IMAGES USING A VARIATIONAL AUTOENCODER CONDITIONED ON SENTINEL-2 IMAGERY |
| title_fullStr | COLORIZING SENTINEL-1 SAR IMAGES USING A VARIATIONAL AUTOENCODER CONDITIONED ON SENTINEL-2 IMAGERY |
| title_full_unstemmed | COLORIZING SENTINEL-1 SAR IMAGES USING A VARIATIONAL AUTOENCODER CONDITIONED ON SENTINEL-2 IMAGERY |
| title_short | COLORIZING SENTINEL-1 SAR IMAGES USING A VARIATIONAL AUTOENCODER CONDITIONED ON SENTINEL-2 IMAGERY |
| title_sort | colorizing sentinel 1 sar images using a variational autoencoder conditioned on sentinel 2 imagery |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2/1045/2018/isprs-archives-XLII-2-1045-2018.pdf |
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