UnDIP: Hyperspectral Unmixing Using Deep Image Prior

In this article, we introduce a deep learning-based technique for the linear hyperspectral unmixing problem. The proposed method contains two main steps. First, the endmembers are extracted using a geometric endmember extraction method, i.e., a simplex volume maximization in the subspace of the data...

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Bibliographic details
Main Author: Rasti, Behnood
Koirala, Bikram
Scheunders, Paul
Ghamisi, Pedram
Format: Journal Article
Language: English
Place of publication: IEEE 30.03.2021
published in: IEEE transactions on geoscience and remote sensing pp. 1 - 15
ORCID: 0000-0002-1091-9841
0000-0003-2447-4772
0000-0003-1203-741X
0000-0002-8887-8197
Data of publication: 20210330
ISSN: 0196-2892
1558-0644
EISSN: 1558-0644
Discipline: Engineering
Physics
Subjects:
Online Access: available in Bonn?
CODEN: IGRSD2
Database: Database information not found
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