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Learning A Low-Coherence Dictionary to Address Spectral Variability for Hyperspectral Unmixing

Hong, Danfeng and Yokoya, Naoto and Chanussot, Jocelyn and Zhu, Xiaoxiang (2017) Learning A Low-Coherence Dictionary to Address Spectral Variability for Hyperspectral Unmixing. In: 2017 IEEE International Conference on Image Processing (ICIP), pp. 1-5. IEEE Xplore. International Conference on Image Processing (ICIP 2017), 17.-20. Sep. 2017, Beijing, China.

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This paper presents a novel spectral mixture model to address spectral variability in inverse problems of hyperspectral unmixing. Based on the linear mixture model (LMM), our model introduces a spectral variability dictionary to account for any residuals that cannot be explained by the LMM. Atoms in the dictionary are assumed to be low-coherent with spectral signatures of endmembers. A dictionary learning technique is proposed to learn the spectral variability dictionary while solving unmixing problems simultaneously. Experimental results on synthetic and real datasets demonstrate that the performance of the proposed method is superior to state-of-the-art methods.

Item URL in elib:https://elib.dlr.de/112774/
Document Type:Conference or Workshop Item (Speech)
Title:Learning A Low-Coherence Dictionary to Address Spectral Variability for Hyperspectral Unmixing
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Hong, Danfengdanfeng.hong (at) dlr.deUNSPECIFIED
Yokoya, Naotonaoto.yokoya (at) dlr.deUNSPECIFIED
Chanussot, Jocelynjocelyn (at) hi.isUNSPECIFIED
Zhu, Xiaoxiangxiao.zhu (at) dlr.deUNSPECIFIED
Journal or Publication Title:2017 IEEE International Conference on Image Processing (ICIP)
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-5
EditorsEmailEditor's ORCID iD
Publisher:IEEE Xplore
Keywords:Remote sensing, spectral unmixing, spectral variability, low-coherent dictionary learning, alternating direction method of multipliers.
Event Title:International Conference on Image Processing (ICIP 2017)
Event Location:Beijing, China
Event Type:international Conference
Event Dates:17.-20. Sep. 2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Hong, Danfeng
Deposited On:20 Jun 2017 15:40
Last Modified:15 Dec 2017 17:11

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