Reconstruction from Spatio-Spectrally Coded Multispectral Light Fields
| dc.contributor.author | Schambach, Maximilian | |
| dc.date.accessioned | 2022-10-25T09:32:05Z | |
| dc.date.available | 2022-10-25T09:32:05Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | https://library.oapen.org/handle/20.500.12657/59047 | |
| dc.description.abstract | In this work, spatio-spectrally coded multispectral light fields, as taken by a light field camera with a spectrally coded microlens array, are investigated. For the reconstruction of the coded light fields, two methods, one based on the principles of compressed sensing and one deep learning approach, are developed. Using novel synthetic as well as a real-world datasets, the proposed reconstruction approaches are evaluated in detail. | en_US |
| dc.language | English | en_US |
| dc.relation.ispartofseries | Forschungsberichte aus der Industriellen Informationstechnik | en_US |
| dc.subject.classification | thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering | en_US |
| dc.subject.other | Computer Vision; Lichtfelder; Multispektrale Bildgebung; Compressed Sensing; Deep Learning; computer vision; light fields; multispectral imaging; compressed sensing; deep learning | en_US |
| dc.title | Reconstruction from Spatio-Spectrally Coded Multispectral Light Fields | en_US |
| dc.type | book | |
| oapen.identifier.doi | 10.5445/KSP/1000148072 | en_US |
| oapen.relation.isPublishedBy | 44e29711-8d53-496b-85cc-3d10c9469be9 | en_US |
| oapen.series.number | 27 | en_US |
| oapen.pages | 238 | en_US |
