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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.
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 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., “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, 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., “Multi-dimensional Pixel Purity Index”, in IEEE-WHISPERS 2013, Workshop on Hyperspectral Image and Signal Processing, Gainesville, Florida, June 25-28, 2013.
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, 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., “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., “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, Akhter, M. A., and Scheunders, P., “A fast alternative for the pixel purity index algorithm”, in IEEE IGARSS 2015, International Geoscience and Remote Sensing Symposium, Milan, Italy, July 26-31, 2015, pp. 1781-1784.
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.
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.
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.
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.
C. C. Hung, Coleman, T., and Scheunders, P., “The genetic algorithm approach and K-means clustering: their role in unsupervised training in image classification”, in Proc. IASTED International Conf. On Computer Graphics and Imaging , Halifax, Canada, june 1-3, 1998, pp. 103-106.
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.
B. Huyge, Sanctorum, J., Six, N., De Beenhouwer, J., and Sijbers, J., “Analysis of flat fields in edge illumination phase contrast imaging”, in 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), Nice, France, 2021, pp. 1310-1313.PDF icon Download paper (368.24 KB)

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