Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Jakub Bieniarz"'
Publikováno v:
Remote Sensing, Vol 7, Iss 10, Pp 13190-13207 (2015)
This paper proposes the use of spectral unmixing and sparse reconstruction methods to restore a simulated dataset for the Environmental Mapping and Analysis Program (EnMAP), the forthcoming German spaceborne hyperspectral mission. The described metho
Externí odkaz:
https://doaj.org/article/b30775de8ad643519b9d40a440d1f5e1
Autor:
Ferran Gascon, Catherine Bouzinac, Olivier Thépaut, Mathieu Jung, Benjamin Francesconi, Jérôme Louis, Vincent Lonjou, Bruno Lafrance, Stéphane Massera, Angélique Gaudel-Vacaresse, Florie Languille, Bahjat Alhammoud, Françoise Viallefont, Bringfried Pflug, Jakub Bieniarz, Sébastien Clerc, Laëtitia Pessiot, Thierry Trémas, Enrico Cadau, Roberto De Bonis, Claudia Isola, Philippe Martimort, Valérie Fernandez
Publikováno v:
Remote Sensing, Vol 9, Iss 6, p 584 (2017)
As part of the Copernicus programme of the European Commission (EC), the European Space Agency (ESA) has developed and is currently operating the Sentinel-2 mission that is acquiring high spatial resolution optical imagery. This article provides a de
Externí odkaz:
https://doaj.org/article/974612482ec3446fa213b80a6a30d5b7
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B3, Pp 469-473 (2016)
In this paper we propose a cloud removal algorithm for scenes within a Sentinel-2 satellite image time series based on synthetisation of the affected areas via sparse reconstruction. For this purpose, a clouds and clouds shadow mask must be given. Wi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86d6c6bb9f32f6513e7d53790421b8db
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B3/469/2016/
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B3/469/2016/
Autor:
Ferran Gascon, Angélique Gaudel-Vacaresse, Jakub Bieniarz, Philippe Martimort, Vincent Lonjou, Stephane Massera, Mathieu Jung, Roberto de Bonis, Enrico Cadau, Thierry Tremas, Laetitia Pessiot, Francoise Viallefont, Florie Languille, Jérôme Louis, Bruno Lafrance, Claudia Isola, Bringfried Pflug, Bahjat Alhammoud, Valerie Fernandez, Olivier Thépaut, Benjamin Francesconi, Sébastien Clerc
As part of the Copernicus programme of the European Union (EU), the European Space Agency (ESA) has developed and is currently operating the Sentinel-2 mission that is acquiring high spatial resolution optical imagery. This paper provides a descripti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09ec9afacfe56ec7dad885be48369549
https://doi.org/10.20944/preprints201610.0078.v1
https://doi.org/10.20944/preprints201610.0078.v1
Autor:
Jiaojiao Tian, Peter Reinartz, Florian Beyer, Jakub Bieniarz, Daniele Cerra, Rupert Müller, Thomas Jarmer
In this paper, we propose a cloud removal algorithm for scenes within a satellite image time series based on synthetization of the affected areas via sparse reconstruction. The high spectrotemporal dimensionality of time series allows applying pixel-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::109be4c869472503a70caa5469a12df0
https://elib.dlr.de/100309/
https://elib.dlr.de/100309/
Publikováno v:
IGARSS
Recently, many sparse approximation methods have been applied to solve spectral unmixing problems. These methods in contrast to traditional methods for spectral unmixing are designed to work with large a-prori given spectral dictionaries containing h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a09565d0a5522feb16db77f2f446b8b
https://doi.org/10.1109/igarss.2015.7326411
https://doi.org/10.1109/igarss.2015.7326411
Publikováno v:
WHISPERS
In this paper we apply the Multi-Look Joint Sparsity Fusion algorithm to multisensor image data. Our algorithm at first performs sparse unmixing of the hyperspectral data and selects pixels for a second unmixing of the multispectral image. This is do
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8ccd6f6c93aecd8947a92c8e8948929
https://doi.org/10.1109/whispers.2015.8075400
https://doi.org/10.1109/whispers.2015.8075400
Recent work on hyperspectral image (HSI) unmixing has addressed the use of overcomplete dictionaries by employing sparse models. In essence, this approach exploits the fact that HSI pixels can be associated with a small number of constituent pure mat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c2f10042acc0aca1c914d4208356d04
https://elib.dlr.de/91624/
https://elib.dlr.de/91624/
Publikováno v:
WHISPERS
This paper presents the first results of applying sparse reconstruction methods to restore a simulated dataset for the Environmental Mapping and Analysis Program (EnMAP), the forthcoming German spaceborne hyperspectral mission. Each mage element is i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3eaef41bfd00c661df5b91a40f503de7
https://elib.dlr.de/99268/
https://elib.dlr.de/99268/
Publikováno v:
IGARSS
Relatively low spatial resolution of the space-borne hyper-spectral images (HSI) is the main drawback to derive value added products. Recently, several techniques have been proposed in order to enhance the spatial resolution HSI by means of fusion wi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::032cac597450547e9513cd677ff9e157
https://doi.org/10.1109/igarss.2014.6947017
https://doi.org/10.1109/igarss.2014.6947017