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Restoration of Simulated EnMAP Data through Sparse Spectral Unmixing

Cerra, Daniele and Bieniarz, Jakub and Müller, Rupert and Storch, Tobias and Reinartz, Peter (2015) Restoration of Simulated EnMAP Data through Sparse Spectral Unmixing. Remote Sensing, 7 (10), pp. 13190-13207. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/rs71013190 ISSN 2072-4292

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Official URL: http://www.mdpi.com/2072-4292/7/10/13190

Abstract

This paper proposes the use of spectral unmixing and sparse reconstruction methods to restore a simulated dataset for the Environmental Mapping and Analysis Program (EnMAP), the forthcoming German spaceborne hyperspectral mission. The described method independently decomposes each image element into a set of representative spectra, which come directly from the image and have previously undergone a low-pass filtering in noisy bands. The residual vector from the unmixing process is considered as mostly composed of noise and ignored in the reconstruction process. The first assessment of the results is encouraging, as the original bands taken into account are reconstructed with a high signal-to-noise ratio and low overall distortions. Furthermore, the same method could be applied for the inpainting of dead pixels, which could affect EnMAP data, especially at the end of the satellite’s life cycle.

Item URL in elib:https://elib.dlr.de/98855/
Document Type:Article
Title:Restoration of Simulated EnMAP Data through Sparse Spectral Unmixing
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Cerra, Danieledaniele.cerra (at) dlr.deUNSPECIFIED
Bieniarz, Jakubjakub.bieniarz (at) dlr.deUNSPECIFIED
Müller, Rupertrupert.mueller (at) dlr.deUNSPECIFIED
Storch, Tobiastobias.storch (at) dlr.deUNSPECIFIED
Reinartz, Peterpeter.reinartz (at) dlr.deUNSPECIFIED
Date:5 October 2015
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:No
Volume:7
DOI :10.3390/rs71013190
Page Range:pp. 13190-13207
Editors:
EditorsEmail
Thenkabail, Prasad S.thenkabail@gmail.com
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:Published
Keywords:EnMAP; denoising; spectral unmixing; sparse reconstruction; inpainting; dead pixels
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Cerra, Daniele
Deposited On:29 Oct 2015 13:31
Last Modified:21 Nov 2019 05:04

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