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Remote sensing

Multispectral and hyperspectral satellite and aerial image processing and analysis

The feasibility of short-wave infrared spectrometry in assessing water-to-cement ratio and density of hardened concrete

Z. Zahiri, Laefer, D., and Gowen, A., “The feasibility of short-wave infrared spectrometry in assessing water-to-cement ratio and density of hardened concrete”, Construction and Building Materials, 2018.

Using Short-wave Infrared Range Spectrometry Data to Determine Brick Characteristics

D. Laefer, Zahiri, Z., and Gowen, A., “Using Short-wave Infrared Range Spectrometry Data to Determine Brick Characteristics”, INTERNATIONAL JOURNAL OF ARCHITECTURAL HERITAGE, 2018.

Distinguishing Façade Material Change using Hyperspectral Imaging

“Distinguishing Façade Material Change using Hyperspectral Imaging”. 2017.

A supervised method for nonlinear hyperspectral unmixing

B. Koirala, Khodadadzadeh, M., Contreras, C., Zahiri, Z., Gloaguen, R., and Scheunders, P., “A supervised method for nonlinear hyperspectral unmixing”, Remote Sensing, vol. 11, no. 20 , 2019.

Files:

remotesensing-11-02458-v3.pdf

Fractional abundance estimation of mixed and compound materials by hyperspectral imaging.

B. Koirala, Zahiri, Z., Khodadadzadeh, M., and Scheunders, P., “Fractional abundance estimation of mixed and compound materials by hyperspectral imaging.”, in 10th Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS), Sept 2019, Amsterdam, Netherlands, 2019, pp. pp. 1-5.

Files:

fractional_abundance_estimation_of_mixed_and_compound_materials_by_hyperspectral_imaging.pdf

A semi-supervised method for Nonlinear Hyperspectral Unmixing

B. Koirala and Scheunders, P., “A semi-supervised method for Nonlinear Hyperspectral Unmixing”, in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Yokohama, Japan, 2019, 2019, pp. pp. 361-364.

Files:

bikram_koirala_igarss2019.pdf

Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields

V. Andrejchenko, Liao, W., Philips, W., and Scheunders, P., “Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields”, Remote Sensing, vol. 11, 2019.

Files:

remotesensing-11-00624.pdf

Nonlinear hyperspectral unmixing with graphical models

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.

Files:

ACIVS 2013, Advanced Concepts for Intelligent Vision Systems

J. Blanc-Talon, Kazinski, A., Philips, W., Popescu, D., and Scheunders, P., “ACIVS 2013, Advanced Concepts for Intelligent Vision Systems”, Lecture Notes in Computer Science, vol. 8129. 2013.

ACIVS 2015, Advanced Concepts for Intelligent Vision Systems

S. Battiato, Blanc-Talon, J., Gallo, G., Philips, W., Popescu, D., and Scheunders, P., “ACIVS 2015, Advanced Concepts for Intelligent Vision Systems”, Lecture Notes in Computer Science, vol. 9386. 2015.

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