Publications

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Heylen, R., and P. Scheunders, "Multi-dimensional Pixel Purity Index", IEEE-WHISPERS 2013, Workshop on Hyperspectral Image and Signal Processing, Gainesville, Florida, June 25-28, 2013.
Heylen, R., M. Parente, and P. Scheunders, "Pixel purity vertex component analysis", IEEE IGARSS 2017, International Geoscience and Remote Sensing Symposium, Fort Worth, USA, July 23-28, 2017.
Heylen, R., and P. Scheunders, "Calculation of geodesic distances in non-linear mixing models: demonstration on the generalized bilinear model", IEEE Geoscience and Remote Sensing letters, vol. 9, issue 4, pp. 644-648, 2012.
Heylen, R., D. Burazerovic, and P. Scheunders, "A graph-based method for non-linear unmixing of hyperspectral imagery", IEEE IGARSS2010, IEEE International Geoscience and Remote Sensing Symposium, Honolulu, Haway, July 25-30, pp. 197-200, 2010.
Heylen, R., and P. Scheunders, "Hyperspectral intrinsic dimensionality estimation with nearest-neighbor distance ratio's", IEEE JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, issue 2, pp. 570-579, 2013.
Heylen, R., and P. Scheunders, "A fast geometric algorithm for solving the inversion problem in spectral unmixing", IEEE-WHISPERS 2012, Workshop on Hyperspectral Image and Signal Processing, Shanghai, June 4-7, 2012.
Heylen, R., P. Scheunders, A. Rangarajan, and P. Gader, "Nonlinear unmixing by using non-Euclidean metrics in a linear unmixing chain", IEEE-Whispers 2014, Workshop on Hyperspectral Image and Signal Processing, Lausanne, Suisse, 2014.
Heylen, R., M. Parente, and P. Scheunders, "Estimation of the intrinsic dimensionality in hyperspectral imagery via the hubness phenomenon", LVA ICA 2017, International conference on latent variable analysis and signal separation, Grenoble, France, February 21-23, Lecture Notes in Computer Science, vol. 10169, 2017.
Heylen, R., and P. Scheunders, "Nonlinear barycentric dimensionality reduction", IEEE ICIP10, IEEE International Conference on Image Processing, Hong Kong, september 26-29, pp. 1341-1344, 2010.
Heylen, R., and P. Scheunders, "A distance geometric framework for non-linear hyperspectral unmixing", IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 1879-1888, 2014.
Heylen, R., M A. Akhter, and P. Scheunders, "A fast alternative for the pixel purity index algorithm", IEEE IGARSS 2015, International Geoscience and Remote Sensing Symposium, Milan, Italy, July 26-31, pp. 1781-1784, 2015.
Heylen, R., M A. Akhter, and P. Scheunders, "On using projection onto convex sets for solving the hyperspectral unmixing problem", IEEE Geoscience and Remote Sensing Letters, 2013.
Heylen, R., and P. Scheunders, "Non-linear fully-constrained spectral unmixing", IEEE IGARSS2011, IEEE International Geoscience and Remote Sensing Symposium, Vancouver, July 25-29, 2011.
Heylen, R., V. Andrejchenko, Z. Zahiri, M. Parente, and P. Scheunders, "Nonlinear hyperspectral unmixing with graphical models", IEEE Transaction on Geoscience and Remote Sensing, 2019.
Heylen, R., P. Scheunders, P. Gader, and A. Rangarajan, "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.
Hufkens, K., R. Ceulemans, and P. Scheunders, "Estimating the ecotone width in patchy ecotones using a sigmoid wave approach", Ecological Informatics, vol. 3, pp. 97-104, 2008.
Hufkens, K., R. Ceulemans, and P. Scheunders, "Ecotones in vegetation ecology: methodology and definitions revisited", Ecological Research, vol. 24, pp. 977-986, 2009.
Hufkens, K., G. Thoonen, J. Vanden Borre, P. Scheunders, and R. Ceulemans, "Habitat reporting of a heathland site: Classification probabilities as additional information, a case study", Ecological Informatics, vol. 5, no. 4, pp. 248 - 255, 2010.
Hufkens, K., P. Scheunders, and R. Ceulemans, "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.
Huijs, S., T. Huysmans, A. De Jong, N. Arnout, J. Sijbers, and J. Bellemans, "Principal component analysis as a tool for determining optimal tibial baseplate geometry in modern TKA design", Acta Orthop Belg, vol. 84, issue 4, pp. 452-460, 2018.
Hung, C. C., T. Coleman, and P. Scheunders, "Using genetic differential competitive learning for unsupervised training in multispectral image classification systems", Proceedings IEEE International Conference on Systems, Man, and Cybernetics , San Diego, California, October 11-14, pp. 4482-4485, 1998.
Hung, C. C., T. Coleman, and P. Scheunders, "The genetic algorithm approach and K-means clustering: their role in unsupervised training in image classification", Proc. IASTED International Conf. On Computer Graphics and Imaging , Halifax, Canada, june 1-3, pp. 103-106, 1998.
Hung, C. C., P. Scheunders, M. Pham, M. C. Su, and T. Coleman, "Using Intelligent Optimization Techniques in the K-means Algorithm for Multispectral Image Classification", International Journal of Fuzzy Systems, vol. 6, no. 3, pp. 107-117, 2004.
Huysmans, T., J. Sijbers, and B. Verdonk, "Statistical shape models for tubular objects", Proceedings of IEEE BENELUX/DSP Valley Signal Processing Symposium (SPS-DARTS), Antwerp, Belgium, pp. 155-158, March, 2006. PDF icon Full text (1.06 MB)
Huysmans, T., J. Sijbers, and F. Verstreken, Orthosis, , no. WO/2016/181282, 2016.

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