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dc.contributor.author
Kiani Shahvandi, Mostafa
dc.date.accessioned
2021-08-10T13:32:06Z
dc.date.available
2021-01-05T11:34:56Z
dc.date.available
2021-05-26T09:06:50Z
dc.date.available
2021-08-10T13:32:06Z
dc.date.issued
2020
dc.identifier.uri
http://hdl.handle.net/20.500.11850/459462
dc.description.abstract
In this paper a new method of image smoothing for satellite imagery and its applications in environmental remote sensing are presented. This method is based on the global gradient minimization over the whole image. With respect to the image discrete identity, the continuous minimization problem is discretized. Using the finite difference numerical method of differentiation, a simple yet efficient 5 × 5-pixel template is derived. Convolution of the derived template with the image in different bands results in the discrimination of various image elements. This method is extremely fast, besides being highly precise. A case study is presented for the northern Iran, covering parts of the Caspian Sea. Comparison of the method with the usual Laplacian template reveals that it is more capable of distinguishing phenomena in the image.
en_US
dc.language.iso
en
en_US
dc.subject
Image classification
en_US
dc.subject
Multispectral satelite imagery
en_US
dc.subject
Laplacian
en_US
dc.subject
Gradient norm minimization
en_US
dc.subject
Environmental remote sensing
en_US
dc.title
Identification and Classification of Phenomena in Multispectral Satellite Imagery Using a New Image Smoother Method and its Applications in Environmental Remote Sensing
en_US
dc.type
Other Conference Item
ethz.event
2nd International Congress on Engineering, Technology & Innovation
en_US
ethz.event.location
Darmstadt, Germany
en_US
ethz.event.date
April 24-26, 2020
en_US
ethz.publication.status
unpublished
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02647 - Inst. f. Geodäsie und Photogrammetrie / Institute of Geodesy and Photogrammetry::09707 - Soja, Benedikt / Soja, Benedikt
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02647 - Inst. f. Geodäsie und Photogrammetrie / Institute of Geodesy and Photogrammetry::09707 - Soja, Benedikt / Soja, Benedikt
en_US
ethz.date.deposited
2021-01-05T11:35:04Z
ethz.source
FORM
ethz.eth
no
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2021-08-10T13:32:14Z
ethz.rosetta.lastUpdated
2022-03-29T11:00:25Z
ethz.rosetta.versionExported
true
ethz.COinS
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