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Feature Enhanced Imaging with Compressed Fractional SAR Sensors: Inverse Problem Formalism and l2–l1 Structured Descriptive Regularization Framework

Shkvarko, Yuriy and Reigber, Andreas and Garcia, Guillermo (2016) Feature Enhanced Imaging with Compressed Fractional SAR Sensors: Inverse Problem Formalism and l2–l1 Structured Descriptive Regularization Framework. In: Proceedings of the European Synthetic Aperture Radar Conference EUSAR 2016. VDE. European Conference on Synthetic Aperture Radar (EUSAR), 2016-06-06 - 2016-06-09, Hamburg, Germany.

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Item URL in elib:https://elib.dlr.de/103700/
Document Type:Conference or Workshop Item (Speech)
Title:Feature Enhanced Imaging with Compressed Fractional SAR Sensors: Inverse Problem Formalism and l2–l1 Structured Descriptive Regularization Framework
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Shkvarko, YuriyNational Polythecnic Institute, MexicoUNSPECIFIED
Reigber, AndreasUNSPECIFIEDUNSPECIFIED
Garcia, GuillermoCUCEI, MexicoUNSPECIFIED
Date:2016
Journal or Publication Title:Proceedings of the European Synthetic Aperture Radar Conference EUSAR 2016
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Publisher:VDE
Status:Published
Keywords:SAR
Event Title:European Conference on Synthetic Aperture Radar (EUSAR)
Event Location:Hamburg, Germany
Event Type:international Conference
Event Dates:2016-06-06 - 2016-06-09
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 Flugzeug-SAR
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute > SAR Technology
Deposited By: Reigber, Prof. Dr. Andreas
Deposited On:01 Apr 2016 09:22
Last Modified:15 Nov 2016 16:14

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