Publications

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Journal Article
B. Koirala, Khodadadzadeh, M., Contreras, C., Zahiri, Z., Gloaguen, R., and Scheunders, P., “A supervised method for nonlinear hyperspectral unmixing”, Remote Sensing, vol. 11, no. 20 , 2019.PDF icon remotesensing-11-02458-v3.pdf (3.23 MB)
B. Koirala, Mboga, N., Moelans, R., Knaeps, E., Sels, S., Winters, F., Samsonova, S., Vanlanduit, S., and Scheunders, P., “Study on the Potential of Oil Spill Monitoring in a Port Environment Using Optical Reflectance”, Remote Sensing, 2023.PDF icon remotesensing-15-04950_1.pdf (20.86 MB)
G. Van de Wouwer, Scheunders, P., and Van Dyck, D., “Statistical texture characterization from discrete wavelet representations”, IEEE Transactions on Image Processing, vol. 8, pp. 592-598, 1999.
D. Burazerovic, Heylen, R., Raymaekers, D., Knaeps, E., and Scheunders, P., “A spectral-unmixing approach to estimate water-mass concentrations in case-II waters”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, 2014.
V. Van Meir, Boumans, T., De Groof, G., Van Audekerke, J., Smolders, A., Scheunders, P., Sijbers, J., Verhoye, M., Balthazart, J., and Van Der Linden, A., “Spatiotemporal properties of the BOLD response in the songbirds auditory circuit during a variety of listening tasks”, NeuroImage, vol. 25, pp. 1242-1255, 2005.
E. K. Ghasrodashti, Karami, A., Heylen, R., and Scheunders, P., “Spatial Resolution Enhancement of Hyperspectral Images Using Spectral Unmixing and Bayesian Sparse Representation”, Remote Sensing, vol. 9, no. 6, 2017.
G. Liu, Nath, T., Guo, Z., Linneweber, G., Claeys, A., Li, J., Bengochea, M., De Backer, S., Weyn, B., Sneyders, M., Nicasy, H., Yu, P., Scheunders, P., and Hassan, B., “A simple computer vision pipeline reveals the effects of isolation on social interaction dynamics in Drosophila”, Plos Computational Biology, vol. 14, no. 8, p. e1006410, 2018.
G. Zhang, Scheunders, P., Cerra, D., and Muller, R., “Shadow-aware nonlinear spectral unmixing for hyperspectral imagery”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 5514-5533, 2022.PDF icon shadow-aware_nonlinear_spectral_unmixing_for_hyperspectral_imagery.pdf (9.51 MB)
W. Liao, Pizurica, A., Scheunders, P., Philips, W., and Pi, Y., “Semi-supervised local discriminant analysis for feature extraction in hyperspectral images”, IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 1, pp. 184-198, 2013.
B. Koirala, Zahiri, Z., Lamberti, A., and Scheunders, P., “Robust supervised method for nonlinear spectral unmixing accounting for endmember variability”, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 9, pp. 7434-7448, 2021.PDF icon ieee_version.pdf (3.76 MB)
B. Koirala, Zahiri, Z., and Scheunders, P., “A Robust Supervised Method for Estimating Soil Moisture Content From Spectral Reflectance”, IEEE Transactions on Geoscience and Remote Sensing , vol. 60, pp. 1-13, 2022.PDF icon soil_moisture_content.pdf (7.95 MB)
J. Sijbers, Scheunders, P., Bonnet, N., Van Dyck, D., and Raman, E., “Quantification and improvement of the signal-to-noise ratio in a magnetic resonance image acquisition procedure”, Magnetic Resonance Imaging, vol. 14, pp. 1157-1163, 1996.PDF icon Download paper (1.31 MB)
P. Scheunders, “An orthogonal wavelet representation of multivalued images”, IEEE Transactions on Image Processing, vol. 12, pp. 718-725, 2003.
M. Baillieux and Scheunders, P., “On-line determination of the velocity of simultaneously moving organisms by image analysis for the detection of sublethal toxicity”, Water Research, vol. 32, pp. 1027-1034, 1998.
R. Heylen, Scheunders, P., Gader, P., and Rangarajan, A., “Nonlinear unmixing by using different metrics in a linear unmixing chain”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015.
R. Heylen, Burazerovic, D., and Scheunders, P., “Nonlinear spectral unmixing by geodesic simplex volume maximization”, IEEE Journal of Selected Topics in Signal Processing, vol. 5, pp. 534-542, 2011.
P. Scheunders, De Backer, S., and Naud, A., “Non-linear mapping for feature extraction”, Lecture Notes in Computer Science, vol. 1451, pp. 823-830, 1998.
R. Heylen, Andrejchenko, V., Zahiri, Z., Parente, M., and Scheunders, P., “Nonlinear hyperspectral unmixing with graphical models”, IEEE Transaction on Geoscience and Remote Sensing, vol. 57, no. 7, pp. 4844-4856, 2019.PDF icon published.pdf (3.15 MB)
S. De Backer, Naud, A., and Scheunders, P., “Non-linear Dimensionality Reduction Techniques for Unsupervised Feature Extraction”, Pattern Recognition Letters, vol. 19, pp. 711-720, 1998.
M. Shahrimie Asaari, Mertens, S., Verbraeken, L., Dhondt, S., Inze, D. G., Koirala, B., and Scheunders, P., “Non-destructive analysis of plant physiological traits using hyperspectral imaging: A case study on drought stress”, Computers and Electronics in Agriculture, vol. 195, 2022.
M. Shahrimie Asaari, Mertens, S., Verbraeken, L., Dhondt, S., Inze, D., Koirala, B., and Scheunders, P., “Non-Destructive Analysis of Plant Physiological Traits Using Hyperspectral Imaging: A Case Study on Drought Stress”, Computers and Electronics in Agriculture, vol. 195, no. 106806, 2022.PDF icon 1-s2.0-s0168169922001235-main.pdf (5.53 MB)
Y. Zhang, De Backer, S., and Scheunders, P., “Noise-resistant wavelet-based Bayesian fusion of multispectral and hyperspectral images”, IEEE Transactions on Geoscience and Remote Sensing, vol. 47, pp. 3834-3843, 2009.
B. Rasti, Scheunders, P., Ghesami, P., Licciardi, G., and Chanussot, J., “Noise reduction in hyperspectral imagery: overview and application”, Remote Sensing , vol. 10, no. 3, p. 482, 2018.
P. Scheunders, “A multivalued image wavelet representation based on multiscale fundamental forms”, IEEE Transactions on Image Processing, vol. 11, pp. 568-575, 2002.
G. Thoonen, Mahmood, Z., Peeters, S., and Scheunders, P., “Multisource classification of color and hyperspectral images using color attribute profiles and composite decision fusion”, Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, vol. 5, pp. 510 - 521, 2012.

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