Linear Inverse Problem (LIP) Optimisation for Remote Sensing Applications - Spectral Reconstruction

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dc.contributor.authorChatterjee, Ayan
dc.date.accessioned2024-05-05T11:13:08Z
dc.date.available2024-05-05T11:13:08Z
dc.date.issued2018-11-15 13:26
dc.description.abstract3MT presented at the 2018 Defence and Security Doctoral Symposium.Remote sensing applications like classification and target detection, particularly for high demanded applications such as the detection of difficult targets from cluttered scene, depends on relevant wavelengths of information. While multispectral imagery in airborne or spaceborne platforms consists of a few wavelengths far apart from each other (usually less than 20 bands), which is found not sufficient enough. This project explores new concepts for using not only spatial/spectral information, but also to extract new information from the few bands in the input data for an enhanced spectral mixture analysis.
dc.description.sponsorshipDstl
dc.identifier.citationChatterjee, Ayan (2018). Linear Inverse Problem (LIP) Optimisation for Remote Sensing Applications - Spectral Reconstruction. Cranfield Online Research Data (CORD). Presentation. https://doi.org/10.17862/cranfield.rd.7346627.v1
dc.identifier.doi10.17862/cranfield.rd.7346627.v1
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/21483
dc.publisherCranfield University
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject'Spectral reconstruction'
dc.subject'Inverse problem'
dc.subject'Hyperspectral'
dc.subject'DSDS18 3MT'
dc.subject'DSDS18'
dc.subject'Photogrammetry and Remote Sensing'
dc.titleLinear Inverse Problem (LIP) Optimisation for Remote Sensing Applications - Spectral Reconstruction
dc.typePresentation

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