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Remote sensing

Multispectral and hyperspectral satellite and aerial image processing and analysis

A NEURAL NETWORK METHOD FOR NONLINEAR HYPERSPECTRAL UNMIXING

B. Koirala, Heylen, R., and Scheunders, P., “A NEURAL NETWORK METHOD FOR NONLINEAR HYPERSPECTRAL UNMIXING”, in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, 2018, pp. pp. 4233-4236.

Files:

a_nn_method_bikram_koirala_igarss2018.pdf

Latent Heat Loss of a Virtual Thermal Manikin for Evaluating the Thermal Performance of Bicycle Helmets

S. Mukunthan, Vleugels, J., Huysmans, T., and De Bruyne, G., “Latent Heat Loss of a Virtual Thermal Manikin for Evaluating the Thermal Performance of Bicycle Helmets”, in Advances in Human Factors in Simulation and Modeling, Cham, 2019, pp. 66–78.

Lidar information extraction by attribute filters with partial reconstruction

W. Liao, M Mura, D., Huang, X., Chanussot, J., Gautama, S., Scheunders, P., and Philips, W., “Lidar information extraction by attribute filters with partial reconstruction”, in IEEE IGARSS 2016, International Geoscience and Remote Sensing Symposium, pp. 1484-1487, Beijing, July 10-15 , 2016.

Alternating angle minimization based unmixing with endmember variability

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.

Pixel purity vertex component analysis

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.

Estimation of the intrinsic dimensionality in hyperspectral imagery via the hubness phenomenon

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.

Evaluating palmiet wetland decline: a comparison of three methods

A. J. Rebelo, Scheunders, P., Esler, K. J., and Meire, P., “Evaluating palmiet wetland decline: a comparison of three methods”, Remote Sensing Applications: Society and Environment, vol. 8, pp. 212-223, 2017.

On the use of dorsiventral reflectance asymmetry of hornbeam (Carpinus betulus L.) leaves in air pollution estimation

M. Brackx, Verhelst, J., Scheunders, P., and Samson, R., “On the use of dorsiventral reflectance asymmetry of hornbeam (Carpinus betulus L.) leaves in air pollution estimation”, Environmental Monitoring and Assessment, vol. 189, no. 9, 2017.

Spatial Resolution Enhancement of Hyperspectral Images Using Spectral Unmixing and Bayesian Sparse Representation

E. K. Ghasrodashti, Karami, A., Heylen, R., and Scheunders, P., “Spatial Resolution Enhancement of Hyperspectral Images Using Spectral Unmixing and Bayesian Sparse Representation”, Remote Sensing, vol. 9, no. 6, 2017.

Fusion of Hyperspectral and LiDAR Data for Classification of Cloud-Shadow Mixed Remote Sensing Scene

R. Luo, Liao, W., Zhang, H., Zhang, L., Pi, Y., Scheunders, P., and Philips, W., “Fusion of Hyperspectral and LiDAR Data for Classification of Cloud-Shadow Mixed Remote Sensing Scene”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 8, pp. 3768-3781, 2017.

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