Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Tatsumi Uezato"'
Publikováno v:
Remote Sensing, Vol 12, Iss 14, p 2326 (2020)
Accounting for endmember variability is a challenging issue when unmixing hyperspectral data. This paper models the variability that is associated with each endmember as a conical hull defined by extremal pixels from the data set. These extremal pixe
Externí odkaz:
https://doaj.org/article/400fba97182b411d9c4e698645baad5c
Publikováno v:
IEEE Transactions on Computational Imaging. 9:185-196
Publikováno v:
IEEE Transactions on Image Processing. 29:3652-3664
Although many spectral unmixing models have been developed to address spectral variability caused by variable incident illuminations, the mechanism of the spectral variability is still unclear. This paper proposes an unmixing model, named illuminatio
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031197994
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae56eca1ac7410b94c20157fe48b8559
https://doi.org/10.1007/978-3-031-19800-7_2
https://doi.org/10.1007/978-3-031-19800-7_2
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031197994
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a985198ae9549e720dc30520646841f9
https://doi.org/10.1007/978-3-031-19800-7_1
https://doi.org/10.1007/978-3-031-19800-7_1
Publikováno v:
Deep Learning for the Earth Sciences
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ecd929a26bb86ed68edbad5383bfb1c
https://hdl.handle.net/11367/114864
https://hdl.handle.net/11367/114864
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing
IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2019, 57 (6), pp.3980-3992. ⟨10.1109/TGRS.2018.2889256⟩
IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2019, 57 (6), pp.3980-3992. ⟨10.1109/TGRS.2018.2889256⟩
International audience; Spectral variability is one of the major issue when conducting hyperspectral unmixing. Within a given image composed of some elementary materials (herein referred to as endmember classes), the spectral signature characterizing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::812f7416a998b789319efb063ee684a6
https://hal.archives-ouvertes.fr/hal-01797092
https://hal.archives-ouvertes.fr/hal-01797092
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585389
ECCV (6)
ECCV (6)
The fusion of input and guidance images that have a tradeoff in their information (e.g., hyperspectral and RGB image fusion or pansharpening) can be interpreted as one general problem. However, previous studies applied a task-specific handcrafted pri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d964b086a5b42ce5f3f393dc0d62d06
http://arxiv.org/abs/2007.11766
http://arxiv.org/abs/2007.11766
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 54:6712-6731
Spectral variability, unrelated to the purity of endmembers, can change the geometry of the dataspace and affect conventional methods used to identify endmembers. Several methods have been developed to identify and extract endmember bundles represent
Publikováno v:
WHISPERS
Hyperspectral unmixing has attained a great importance in recent decades in remote sensing applications. Due to some external effect (illumination conditions) or internal effects (concentration of chlorophyll), spectral variability exists in hyperspe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::450b32b2acdfff43f1cde3814e81594b
https://aperta.ulakbim.gov.tr/record/70065
https://aperta.ulakbim.gov.tr/record/70065