A
Asgeir Bjorgan
Researcher at Norwegian University of Science and Technology
Publications - 17
Citations - 196
Asgeir Bjorgan is an academic researcher from Norwegian University of Science and Technology. The author has contributed to research in topics: Hyperspectral imaging & Image resolution. The author has an hindex of 7, co-authored 17 publications receiving 159 citations.
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Estimation of skin optical parameters for real-time hyperspectral imaging applications
TL;DR: An analytic diffusion model for photon transport with real-time analysis of the hyperspectral images is combined by parallelizing the inverse photon transport model on a graphics processing unit to yield optical parameters from diffuse reflectance spectra.
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Mirror Mirror on the Wall... An Unobtrusive Intelligent Multisensory Mirror for Well-Being Status Self-Assessment and Visualization
Pedro Henriquez,Bogdan J. Matuszewski,Yasmina Andreu,Luca Bastiani,Sara Colantonio,Giuseppe Coppini,Mario D’Acunto,Riccardo Favilla,Danila Germanese,Daniela Giorgi,Paolo Marraccini,Massimo Martinelli,Maria-Aurora Morales,Maria Antonietta Pascali,Marco Righi,Ovidio Salvetti,Marcus Larsson,Tomas Strömberg,Lise Lyngsnes Randeberg,Asgeir Bjorgan,Giorgos Giannakakis,Matthew Pediaditis,Franco Chiarugi,Eirini Christinaki,Kostas Marias,Manolis Tsiknakis +25 more
TL;DR: SEMEOTICONS developed a multisensory platform in the form of a smart mirror to identify signs related to cardio-metabolic risk and enable users to self-monitor their well-being status over time and guide them to improve their lifestyle.
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Real-time noise removal for line-scanning hyperspectral devices using a minimum noise fraction-based approach.
TL;DR: With a satisfying denoising performance and real-time implementation, the developed algorithm can denoise line-scanned hyperspectral images in real-Time and the elimination of waiting time before denoised data are available is an important step towards real- time visualization of processed hyperspectrals data.
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Can spectral–spatial image segmentation be used to discriminate experimental burn wounds?
Lukasz A. Paluchowski,Håvard Nordgaard,Asgeir Bjorgan,Håkon Hov,Sissel Marie Berget,Lise Lyngsnes Randeberg +5 more
TL;DR: The results of this study indicate that unsupervised spectral–spatial segmentation applied on hyperspectral images can discriminate burn injuries of varying severity.
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Wavelet based feature extraction and visualization in hyperspectral tissue characterization
TL;DR: Wavelet analysis appears as a promising tool for extraction of spectral features in skin with a significant correlation between the chosen tissue parameters and the selected wavelet components.