Marius Pedersen
Background and activities
Marius Pedersen received his BsC in Computer Engineering in 2006, and MiT in Media Technology in 2007, both from Gjøvik University College, Norway. He completed a PhD program in color imaging in 2011 from the University of Oslo, Norway, sponsored by Océ. He is professor at the Department of Computer Science at NTNU in Gjøvik, Norway. He is also the director of the Norwegian Colour and Visual Computing Laboratory (Colourlab). His work is centered on subjective and objective image quality.
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
- (2021) Image Quality Assessment without Reference by Combining Deep Learning-Based Features and Viewing Distance. Applied Sciences. vol. 11 (10).
- (2021) The Role of Subsurface Scattering in Glossiness Perception. ACM Transactions on Applied Perception. vol. 18 (3).
- (2021) On the appearance of objects and materials: Qualitative analysis of experimental observations. Journal of the International Colour Association. vol. 27.
2020
- (2020) A Critical Analysis on Perceptual Contrast and its Use in Visual Information Analysis and Processing. IEEE Access. vol. 8.
- (2020) Error reduction through post processing for wireless capsule endoscope video. EURASIP Journal on Image and Video Processing.
- (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) Blind Quality Assessment of Iris Images Acquired in Visible Light for Biometric Recognition. Sensors. vol. 20 (5).
- (2020) Impact of printing surfaces with UV-curable inks on sound absorption. Journal of Print and Media Technology Research. vol. 9 (2).
- (2020) PS-DeVCEM: Pathology-sensitive deep learning model for video capsule endoscopy based on weakly labeled data. Computer Vision and Image Understanding. vol. 201:103062.
- (2020) Semi-supervised Network for Detection of COVID-19 in Chest CT Scans. IEEE Access. vol. 8.
- (2020) Content-based image quality assessment. International journal of imaging and robotics. vol. 20 (3).
- (2020) Using watermark visibility measurements to select an optimized pair of spot colors for use in a binary watermark. IS&T International Symposium on Electronic Imaging Science and Technology.
- (2020) SEENS: Nuclei segmentation in Pap smear images with selective edge enhancement. Future generations computer systems. vol. 114.
2019
- (2019) Do Contrast Measures Correlate? A Pilot Investigation. European Workshop on Visual Information Processing. vol. 2019-October.
- (2019) How Do Image Quality Metrics Perform on Contrast Enhanced Images?. European Workshop on Visual Information Processing. vol. 2019-October.
- (2019) Future Directions in Image Quality. Color and Imaging Conference (CIC).
- (2019) Comparing the Chromatic Contrast Sensitivity in Vertical and Oblique Orientations. Color and Imaging Conference (CIC).
- (2019) Automated salamander recognition using deep neural networks and feature extraction. NIKT: Norsk IKT-konferanse for forskning og utdanning.