Jon Yngve Hardeberg
Background and activities
Jon Yngve Hardeberg (1971) is Professor at the Department of Computer Science at NTNU in Gjøvik. He has a MSc in Signal Processing from NTNU, and a PhD in Signal and Image Processing from the Ecole Nationale Supérieure des Télécommunications in Paris, France.
Professor Hardeberg is a member of the Norwegian Colour and Visual Computing Laboratory where he teaches, supervises graduate students, manages international study programs and research projects. He has co-authored more than 200 publications.
- Multispectral colour imaging
- Print and Image quality
- Colorimetric device characterization
- Colour management
- Cultural heritage imaging
- Medical imaging
Recent Work Experience
- 2008- Chief Scientist, Hardeberg Image and Color Technology, Gjøvik, Norway
- 2017- Professor of Color Imaging, Department of Computer Science, NTNU
- 2016 Professor of Color Imaging, Faculty of Computer Science and Media Technology, NTNU
- 2005-2015 Professor of Color Imaging, Faculty of Computer Science and Media Technology, Gjøvik University College
- 2005-2012 Director, The Norwegian Color Research Laboratory (http://colorlab.no)
- 2001-2005 Associate Professor, Faculty of Computer Science and Media Technology, GUC, Gjøvik, Norway
Professional experience at foreign institutions
- 2017 Fulbright Scholar, Visiting professor (6 months), University of Washington, Seattle, USA
- 2012 Visiting researcher (5 months), Centre de Recherche et de Restauration des musées de France, Paris, France
- 2011 Visiting professor (1 month), Université de Bourgogne, Auxerre, France
- 2011 Visiting professo (1 month), Université Jean Monnet, Saint-Etienne, France
- 2009 Visiting professor, (6 months), University of Washington, Seattle, USA
Recent Institutional Responsibilities
- 2005-2012 Director, The Norwegian Color Research Laboratory
- 2008- Study program director at NTNU Gjøvik and member of the Joint Graduation Committee for the Erasmus Mundus Master Color in Informatics and Media Technology (CIMET) and Colour in Industry and Science (COSI)
- 2007-2009 Head of Section, Color Science and Image Processing, GUC
Commissions of Trust
- Appointed by the National Academies of Sciences, Engineering, and Medicine, he is currently a member of the Standing Committee on Reducing Counterfeiting using the Behavioral Sciences, thus advising the Federal Reserve System in their work of reducing counterfeiting and designing more secure next generation dollar bills
- Chair, Co-Chair, Program chair, Poster chair, sessions chair, scientific committee member, and reviewer for several scientific conferences such as CIC, IARIGAI, MCS, SCIA, EUVIP
- Reviewer for various indexed journals such as Color Research & Application, Journal of Imaging Science and Technology and Optics Express
- Keynote speaker and tutorial speaker at several scientific conferences
- Opponency and review of several master and PhD degree defences
- Associate Editor, Journal of Imaging Science and Technology
Memberships of Scientific Societies
- Division Member representing Norway in the International Commission on Illumination (CIE), Division 8: Image Technology
- 2013-2016 Norway´s Management Committee member in the COST Action TD 1201: Colour and Space in Cultural Heritage (COSCH).
- 2004-2015 Gjøvik University College´s representative in the International Association of Research Organisations for the Printing, Information, and Communication Industries (IARIGAI), International Color Consortium
- 2010- National board member of TEKNA Forskerne (the research section of The Norwegian Society of Graduate Technical and Scientific Professionals)
- 2013- National board member of NOBIM (the Norwegian Society for Image Processing and Pattern Recognition)
- 2013- Chairman and founder of Forum Farge, Norway´s colour association
- 2013- Member of IS&T, SPIE (Senior Member from 2015), IEEE
- 2016-2021 Project leader, research, PhD/postdoc supervision. MUVApp – Measuring and Understanding Visual Appereance. FRINATEK TOPPFORSK project funded by the Research Council of Norway. Total budget NOK 24 978 000
- 2015-2018 PI, research, PhD/postdoc supervision. IQ-MED – Image Quality enhancement in MEDical diagnosis, monitoring and treatment, IKTPLUSS Project funded by the Research Council of Norway. Total budget NOK 16 200 000
- 2012-2016 Project leader, research, PhD/postdoc supervision – HyPerCept: Color and Quality in Higher Dimensions. SHP Project funded the Research Council of Norway. Total budget NOK 33 670 000
- 2012-2015 Project coordinator, research, ESR supervision – Colour Printing 7.0: Next Generation Multi-Channel Printing, EU Project funded by Marie Curie Initial Training Networks. Total budget NOK 2 450 000 Euro
- 2014-2016 Project leader, research – Hyperspectral Imaging and Analysis of Ancient Manuscripts. Project funded by Regional Research Council Innlandet. Total budget NOK 969 000
- 2014-2016 Project leader, research – HyperDerm – Imaging system prototype setup and evaluation. Project funded by Regional Reserch Council Innlandet. Total budget NOK 909 000
Professor Hardeberg has supervised 46 master students, 12 graduated PhD students and is currently supervising 4 Post-Doctoral fellows and 5 PhD students. Since 2001 he has been teaching courses and modules of color science, color management, color imaging, image reproduction, computer graphics, color in display, media representation, compression.
10 selected publications
- V. Cheung, S. Westland, C. Li, J.Y. Hardeberg, D. Connah, “Characterization of trichromatic color cameras by using a new multispectral imaging technique”, Journal of the Optical Society of America A 22 (7), 1231-1240, 2005. Citations: 84.
- M. Pedersen, N. Bonnier, J.Y. Hardeberg, F. Albregtsen, “Attributes of image quality for color prints”, Journal of Electronic Imaging 19 (1), 011016-011016-13, 2010. Citations: 55.
- F. Dugay, I. Farup, J.Y. Hardeberg, “Perceptual evaluation of color gamut mapping algorithms”, Color Research & Application 33 (6), 470-476, 2008. Citations: 49.
- A. Mansouri, F.S. Marzani, J.Y. Hardeberg, P. Gouton,“Optical calibration of a multispectral imaging system based on interference filters”, Optical Engineering 44 (2), 027004-027004-12, 2005. Citations: 40.
- J.B. Thomas, J.Y. Hardeberg, I. Foucherot, P. Gouton,“The PLVC display color characterization model revisited”, Color Research & Application 33 (6), 449-460, 2008. Citations: 34.
- M. Pedersen, J.Y. Hardeberg,“Full-reference image quality metrics: Classification and evaluation”, Foundations and Trends in Computer Graphics and Vision 7 (1), 1-80, 2012. Citations: 25.
- S. Le Moan, A. Mansouri, Y. Voisin, J.Y. Hardeberg,“A constrained band selection method based on information measures for spectral image color visualization”, IEEE Transactions on Geoscience and Remote Sensing, 49 (12), 5104-5115, 2011. Citations: 17.
- F. Deger, A. Mansouri, M. Pedersen, J.Y. Hardeberg and Y. Voisin,“A sensor-data-based denoising framework for hyperspectral images”, Optics Express, 23(3):1938-1950, 2015.
- H. Deborah, N. Richard, and J.Y. Hardeberg,“A comprehensive evaluation on spectral distance functions and metrics for hyperspectral image processing”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015. Citations: 4.
- R. Shrestha and J.Y. Hardeberg, “Spectrogenic imaging: A novel approach to multispectral imaging in an uncontrolled environment”, Optics Express, 22(8):9123-9133, 2014.
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
- (2021) Pre-trained CNN based deep features with hand-crafted features and patient data for skin lesion classification. Lecture Notes in Computer Science (LNCS). vol. 5805.
- (2020) Caustics and Translucency Perception. IS&T International Symposium on Electronic Imaging Science and Technology.
- (2020) Image Statistics as Glossiness and Translucency Predictor in Photographs of Real-world Objects. CEUR Workshop Proceedings. vol. 2688.
- (2020) On the Nature of Perceptual Translucency. Proceedings of the Workshop on Material Appearance Modeling.
- (2020) The effects of source resolution on resolution enhancement through shifted superimposition projection. Journal of the Society for Information Display. vol. 28 (10).
- (2020) Perovskite Color Detectors: Approaching the Efficiency Limit. ACS Applied Materials & Interfaces. vol. 12 (42).
- (2020) A probabilistic bag-to-class approach to multiple-instance learning. Data. vol. 5 (2).
- (2020) LED primary selection algorithms for simulation of CIE standard illuminants. Optics Express. vol. 28 (23).
- (2020) Evaluation of the Data Quality from a Round-Robin Test of Hyperspectral Imaging Systems. Sensors. vol. 20 (14).
- (2020) Evaluation of the data quality from a round-robin test of hyperspectral imaging systems. Sensors. vol. 20 (14).
- (2020) Vertically Stacked Perovskite Detectors for Color Sensing and Color Vision. Advanced Materials Interfaces. vol. 7.
- (2020) Changes in the visual appearance of polychrome wood caused by (accelerated) aging. IS&T International Symposium on Electronic Imaging Science and Technology.
- (2020) Three perceptual dimensions for specular and diffuse reflection. ACM Transactions on Applied Perception. vol. 17 (2).
- (2019) Deep Learning Approaches for Whiteboard Image Quality Enhancement. Journal of Imaging Science and Technology. vol. 63 (4).
- (2019) Evaluating the naturalness and legibility of whiteboard image enhancements. IS&T International Symposium on Electronic Imaging Science and Technology. vol. 2019 (14).
- (2019) A Spectral Filter Array Camera for Clinical Monitoring and Diagnosis: Proof of Concept for Skin Oxygenation Imaging. Journal of Imaging. vol. 5(8).
- (2019) An Evaluation Framework for Spectral Filter Array Cameras to Optimize Skin Diagnosis. Sensors. vol. 19 (21).
- (2019) A Metrological Measurement of Texture in Hyperspectral Images Using Relocated Spectral Difference Occurrence Matrix. Proceedings of IEEE international conference on image processing. vol. 2019-September.
- (2019) A Metrological Framework for Hyperspectral Texture Analysis Using Relative Spectral Difference Occurrence Matrix. Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing. vol. 2019-September.
- (2019) Spectral-divergence based pigment discrimination and mapping: A case study on The Scream (1893) by Edvard Munch. Journal of the American Institute for Conservation. vol. 58 (1-2).