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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, Burazerovic, D., and Scheunders, P., “Fully constrained least-squares spectral unmixing by simplex projection”, IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 11, pp. 4112-4122, 2011.PDF icon PDF (1.11 MB)Package icon Matlab code (1.93 KB)
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, 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 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., “Spectral unmixing using distance geometry”, in IEEE-WHISPERS 2011, Workshop on Hperspectral Image and Signal Processing, Lisbon, Portugal, 6-9 June, 2011.
R. Heylen and Scheunders, P., “Calculation of geodesic distances in non-linear mixing models: demonstration on the generalized bilinear model”, IEEE Geoscience and Remote Sensing letters, vol. 9, no. 4, pp. 644-648, 2012.
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.
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 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 intrinsic dimensionality estimation with nearest-neighbor distance ratio's”, IEEE JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 2, pp. 570-579, 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, 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, Parente, M., and Scheunders, P., “Pixel purity vertex component analysis”, in IEEE IGARSS 2017, International Geoscience and Remote Sensing Symposium, Fort Worth, USA, July 23-28, 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.
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, 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.