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Multi-Source and Multi-Temporal Image Fusion on Hypercomplex Bases

Schmitt, Andreas and Wendleder, Anna and Kleynmans, Rüdiger and Hell, Maximilian and Roth, Achim and Hinz, Stefan (2020) Multi-Source and Multi-Temporal Image Fusion on Hypercomplex Bases. Remote Sensing, 12 (6), pp. 1-37. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/rs12060943 ISSN 2072-4292

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Official URL: https://www.mdpi.com/2072-4292/12/6/943


This article spanned a new, consistent framework for production, archiving, and provision of analysis ready data (ARD) from multi-source and multi-temporal satellite acquisitions and an subsequent image fusion. The core of the image fusion was an orthogonal transform of the reflectance channels from optical sensors on hypercomplex bases delivered in Kennaugh-like elements, which are well-known from polarimetric radar. In this way, SAR and Optics could be fused to one image data set sharing the characteristics of both: the sharpness of Optics and the texture of SAR. The special properties of Kennaugh elements regarding their scaling—linear, logarithmic, normalized—applied likewise to the new elements and guaranteed their robustness towards noise, radiometric sub-sampling, and therewith data compression. This study combined Sentinel-1 and Sentinel-2 on an Octonion basis as well as Sentinel-2 and ALOS-PALSAR-2 on a Sedenion basis. The validation using signatures of typical land cover classes showed that the efficient archiving in 4 bit images still guaranteed an accuracy over 90% in the class assignment. Due to the stability of the resulting class signatures, the fuzziness to be caught by Machine Learning Algorithms was minimized at the same time. Thus, this methodology was predestined to act as new standard for ARD remote sensing data with an subsequent image fusion processed in so-called data cubes.

Item URL in elib:https://elib.dlr.de/134467/
Document Type:Article
Title:Multi-Source and Multi-Temporal Image Fusion on Hypercomplex Bases
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Schmitt, Andreasandreas.schmitt (at) hm.eduUNSPECIFIED
Wendleder, AnnaAnna.Wendleder (at) dlr.deUNSPECIFIED
Kleynmans, Rüdigerrkleynmans (at) web.deUNSPECIFIED
Hell, Maximilianmaximilian.hell (at) hm.eduUNSPECIFIED
Roth, AchimAchim.Roth (at) dlr.deUNSPECIFIED
Hinz, Stefanstefan.hinz (at) kit.eduUNSPECIFIED
Date:14 March 2020
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
DOI :10.3390/rs12060943
Page Range:pp. 1-37
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:Advances in Remote Sensing Image Fusion
Keywords:Kennaugh framework; quaternion; hypercomplex bases; image fusion; time series; change detection; SAR sharpening; data cube; analysis ready data; efficient archiving
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 - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
Deposited By: Wendleder, Anna
Deposited On:19 Mar 2020 13:48
Last Modified:19 Mar 2020 13:48

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