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B. Haest, Vanden Borre, J., Spanhove, T., Thoonen, G., Delalieux, S., Kooistra, L., Mücher, C. A., Paelinckx, D., Scheunders, P., and Kempeneers, P., “Habitat mapping and quality assessment of NATURA 2000 Heatland using airborne imaging spectroscopy”, Remote Sensing, vol. 9, no. 3, 2017.
B. Haest, Thoonen, G., Vanden Borre, J., Spanhove, T., Delalieux, S., Bertels, L., Kooistra, L., Mücher, C. A., and Scheunders, P., “An object-based approach to quantity and quality assessment of heathland habitats in the framework of NATURA 2000 using hyperspectral airborne AHS images.”, in Proceedings of GEOBIA 2010, the Geographic Object-Based Image Analysis Conference, 2010, vol. XXXVIII-4/C7.
J. Hamaide, De Groof, G., Van Steenkiste, G., Jeurissen, B., Van Audekerke, J., Naeyaert, M., Van Ruijssevelt, L., Cornil, C., Sijbers, J., Verhoye, M., and Van Der Linden, A., “ Exploring sex differences in the adult zebra finch brain: In vivo diffusion tensor imaging and ex vivo super-resolution track density imaging”, NeuroImage, vol. 146, pp. 789-803, 2017.
R. Hanel, Batenburg, K. J., and Sijbers, J., “Fast bias field estimation by localized Lloyd-Max quantization”, in SPIE Medical Imaging, San Diego, CA, USA, 2008.PDF icon Download full paper (297.69 KB)
S. Hassanzadeh, Karami, A., Heylen, R., and Scheunders, P., “Compression Of Hyperspectral Images Using Block Coordinate Descent Search And Compressed Sensing”, in 8th workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing, Los Angeles, USA, 2016.
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, Parente, M., and Scheunders, P., “Estimation of the intrinsic dimensionality in hyperspectral imagery via the hubness phenomenon”, in LVA ICA 2017, International conference on latent variable analysis and signal separation, Grenoble, France, February 21-23, Lecture Notes in Computer Science, 2017, vol. 10169.
R. Heylen and Scheunders, P., “Spectral unmixing using distance geometry”, in IEEE-WHISPERS 2011, Workshop on Hperspectral Image and Signal Processing, Lisbon, Portugal, 6-9 June, 2011.
R. Heylen, Scheunders, P., and Gader, P., “Handling spectral variability with alternating angle minimization”, in IEEE-WHISPERS 2013, Workshop on Hyperspectral Image and Signal Processing, Gainesville, Florida, June 25-28, 2013.
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, 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.
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 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 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 and Scheunders, P., “Multi-dimensional Pixel Purity Index”, in IEEE-WHISPERS 2013, Workshop on Hyperspectral Image and Signal Processing, Gainesville, Florida, June 25-28, 2013.
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., “A fast geometric algorithm for solving the inversion problem in spectral unmixing”, in IEEE-WHISPERS 2012, Workshop on Hyperspectral Image and Signal Processing, Shanghai, June 4-7, 2012.
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, 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, Burazerovic, D., and Scheunders, P., “A graph-based method for non-linear unmixing of hyperspectral imagery”, in IEEE IGARSS2010, IEEE International Geoscience and Remote Sensing Symposium, Honolulu, Haway, July 25-30, 2010, pp. 197-200.
R. Heylen, Akhter, M. A., and Scheunders, P., “Solving the Hyperspectral Unmixing Problem with Projection Onto Convex Sets”, in 21st European Signal Processing Conference (EUSIPCO), September 2013, Marrakech, Morocco, 2013.
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, 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.
R. Heylen, Thanki, A., Verhees, D., Iuso, D., De Beenhouwer, J., Sijbers, J., Witvrouw, A., Haitjema, H., and Bey-Temsamani, A., “3D total variation denoising in X-CT imaging applied to pore extraction in additively manufactured parts”, Measurement Science and Technology, vol. 33, no. 4, pp. 1-12, 2022.
R. Heylen and Scheunders, P., “Estimating the number of endmembers in hyperspectral imagery with nearest neighbor distances”, in IEEE IGARSS2012, International Geoscience and Remote Sensing Symposium, Munich, July 22-27, 2012, pp. 1377-1380.

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