Neagoe, Iulia und Faur, Daniela und Vaduva, Corina und Datcu, Mihai (2018) Exploratory Visual Analysis of Multispectral EO Images Based on DNN. In: 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Seiten 1-4. IGARSS 2018, 2018-07-22 - 2018-07-27, Valencia, Spain. doi: 10.1109/IGARSS.2018.8518414.
![]() |
PDF
613kB |
Offizielle URL: https://ieeexplore.ieee.org/document/8518414/authors#authors
Kurzfassung
Exploratory visual analysis is often required to assist human operator to understand and interpret Earth Observation (EO) images. Optimal image representation offers cognitive support in discovering relevant facts about the scene with respect to a particular application. This is of crucial importance for training data sets selection in all Machine Learning tasks, particularly in the design of active learning tools for multispectral (MS) EO data. This paper proposes a deep neural network (DNN) based method to compress, learn and reveal the most significant information included in the spectral bands of EO data in support of relevant visualization for image content analysis. The advanced method uses a DNN to discover the most suggestive pseudo-color representation able to highlight the entire MS image content better than the particular 3 bands selection (R, G, B). We propose the use of information theory and the concept of mutual information to rank the spectral bands based on the amount of information contained, by applying the minimum-redundancy-maximum-relevance (mRMR) criterion on a the image so that we obtain the ranked bands. A DNN stacked autoencoder based paradigm is developed in order to extract and compress in three bands the overall information from the MS EO data. The developed method is demonstrated and validated for Sentinel 2 dataset.
elib-URL des Eintrags: | https://elib.dlr.de/123434/ | ||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||
Titel: | Exploratory Visual Analysis of Multispectral EO Images Based on DNN | ||||||||||||||||||||
Autoren: |
| ||||||||||||||||||||
Datum: | Juli 2018 | ||||||||||||||||||||
Erschienen in: | 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) | ||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||
DOI: | 10.1109/IGARSS.2018.8518414 | ||||||||||||||||||||
Seitenbereich: | Seiten 1-4 | ||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||
Stichwörter: | DNN, minimum-redundancy-maximum-relevance, Sentinel-2 | ||||||||||||||||||||
Veranstaltungstitel: | IGARSS 2018 | ||||||||||||||||||||
Veranstaltungsort: | Valencia, Spain | ||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||
Veranstaltungsbeginn: | 22 Juli 2018 | ||||||||||||||||||||
Veranstaltungsende: | 27 Juli 2018 | ||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Vorhaben hochauflösende Fernerkundungsverfahren (alt) | ||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > EO Data Science | ||||||||||||||||||||
Hinterlegt von: | Dumitru, Corneliu Octavian | ||||||||||||||||||||
Hinterlegt am: | 28 Nov 2018 14:38 | ||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:27 |
Nur für Mitarbeiter des Archivs: Kontrollseite des Eintrags