Publications

Export 1299 results:
[ Author(Desc)] Type Year
Filters: Sparse-unmixing-using-deep-convolutional-networks is   [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
H
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, 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., 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, 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, 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, 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.
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., Multi-dimensional Pixel Purity Index, in IEEE-WHISPERS 2013, Workshop on Hyperspectral Image and Signal Processing, Gainesville, Florida, June 25-28, 2013.
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, 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, 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., 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, 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 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, 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., Nonlinear barycentric dimensionality reduction, in IEEE ICIP10, IEEE International Conference on Image Processing, Hong Kong, september 26-29, 2010, pp. 1341-1344.
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 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, 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., 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.
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)

Pages