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R. Heylen and Scheunders, P., “Nonlinear unmixing with a multilinear mixing model”, in IEEE Whispers 2015, Workshop on Hyperspectral Image and Signal Processing, June 2-5, Tokyo, 2015.
R. Heylen, Zare, A., Gader, P., and Scheunders, P., “Hyperspectral unmixing with endmember variability via alternating angle minimization”, IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 8, pp. 4983-4993, 2016.
R. Heylen and Scheunders, P., “Nonlinear barycentric dimensionality reduction”, in IEEE ICIP10, IEEE International Conference on Image Processing, Hong Kong, september 26-29, 2010, pp. 1341-1344.
R. Heylen and Scheunders, P., “Hyperspectral unmixing using an active set algorithm”, in IEEE ICIP 2014, International Conference on Image Processing, October 27-30, Paris, France , 2014.
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)
R. Heylen, Scheunders, P., Rangarajan, A., and Gader, P., “Nonlinear unmixing by using non-Euclidean metrics in a linear unmixing chain”, in IEEE-Whispers 2014, Workshop on Hyperspectral Image and Signal Processing, Lausanne, Suisse, 2014.
R. Heylen and Scheunders, P., “A multilinear mixing model for nonlinear spectral unmixing”, IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 1, pp. 240-251, 2016.
R. Heylen and Scheunders, P., “A distance geometric framework for non-linear hyperspectral unmixing”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, pp. 1879-1888, 2014.
R. Heylen and Scheunders, P., “Non-linear fully-constrained spectral unmixing”, in IEEE IGARSS2011, IEEE International Geoscience and Remote Sensing Symposium, Vancouver, July 25-29, 2011.
R. Heylen, Akhter, M. A., and Scheunders, P., “On using projection onto convex sets for solving the hyperspectral unmixing problem”, IEEE Geoscience and Remote Sensing Letters, 2013.
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 and Scheunders, P., “Multi-dimensional pixel purity index for convex hull estimation and endmember extraction”, IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 7, pp. 4059-4069, 2013.
R. Heylen, Parente, M., and Scheunders, P., “Estimation of the number of endmembers in a hyperspectral image via the hubness phenomenon”, IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 4, pp. 2191-2200, 2017.
R. Heylen, Scheunders, P., Zare, A., and Gader, P., “Alternating angle minimization based unmixing with endmember variability”, in IEEE IGARSS 2016, International Geoscience and Remote Sensing Symposium, pp. 6974-6977, Beijing, July 10-15 , 2016.
M. Das and Liang, Z., “SPIE ProceedingsSingle-step, quantitative x-ray differential phase contrast imaging using spectral detection in a coded aperture setup”, in SPIE Medical ImagingMedical Imaging 2015: Physics of Medical Imaging, Orlando, Florida, United States, 2015, vol. 9412, p. 941252.
M. Das, Kandel, B., Park, C. Soo, and Liang, Z., “SPIE ProceedingsEnergy calibration of photon counting detectors using x-ray tube potential as a reference for material decomposition applications”, in SPIE Medical ImagingMedical Imaging 2015: Physics of Medical Imaging, Orlando, Florida, United States, 2015, vol. 9412, p. 941214.
S. Hosseinnejad, Bosch, E. G. T., Kohr, H., Lazić, I., Zharinov, V., Franken, E., Sijbers, J., and De Beenhouwer, J., “3D atomic resolution tomography from iDPC-STEM images using multiple atom model prior”, Microscopy Conference. 2021.PDF icon Download abstract (534.35 KB)
T. Hu, Liu, N., Li, W., Tao, R., Zhang, F., and Scheunders, P., “Destriping Hyperspectral Imagery By Adaptive Anisotropic Total Variation And Truncated Nuclear Norm”, in Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2021.
T. Hu, Li, W., Liu, N., Tao, R., Zhang, F., and Scheunders, P., “Hyperspectral Image Restoration Using Adaptive Anisotropy Total Variation and Nuclear Norms”, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 2, pp. 1516-1533, 2021.PDF icon tgrs_2020.pdf (5.71 MB)
K. Hufkens, Ceulemans, R., and Scheunders, P., “Ecotones in vegetation ecology: methodology and definitions revisited”, Ecological Research, vol. 24, pp. 977-986, 2009.
K. Hufkens, Thoonen, G., Vanden Borre, J., Scheunders, P., and Ceulemans, R., “Habitat reporting of a heathland site: Classification probabilities as additional information, a case study”, Ecological Informatics, vol. 5, pp. 248 - 255, 2010.
K. Hufkens, Scheunders, P., and Ceulemans, R., “Validation of the sigmoid wave curve fitting algorithm on a forest-tundra ecotone in the Northwest Territories, Canada”, Ecological Informatics, vol. 4, pp. 1-7, 2009.
K. Hufkens, Ceulemans, R., and Scheunders, P., “Estimating the ecotone width in patchy ecotones using a sigmoid wave approach”, Ecological Informatics, vol. 3, pp. 97-104, 2008.
S. Huijs, Huysmans, T., De Jong, A., Arnout, N., Sijbers, J., and Bellemans, J., “Principal component analysis as a tool for determining optimal tibial baseplate geometry in modern TKA design”, Acta Orthop Belg, vol. 84, no. 4, pp. 452-460, 2018.
C. C. Hung, Coleman, T., and Scheunders, P., “Using genetic differential competitive learning for unsupervised training in multispectral image classification systems”, in Proceedings IEEE International Conference on Systems, Man, and Cybernetics , San Diego, California, October 11-14, 1998, pp. 4482-4485.

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