Remote Sensing

Remote Sensing is the research area in which earth's surface is studied, usually using the reflectance spectrum of the sun. Vision Lab has built expertise in the processing and analysis of multispectral and hyperspectral remote sensing images. Topics of research include the development of techniques for image denoising, restoration, fusion, segmentation, classification and spectral unmixing. Main application domains are vegetation monitoring for which we collaborate with the Teleprocessing group of VITO (Flemish Institute for Technological Research).

Journal publications

2020

B. Koirala, Zahiri, Z., and Scheunders, P., “A Machine Learning Framework for Estimating Leaf Biochemical Parameters From Its Spectral Reflectance and Transmission Measurements”, IEEE Transactions on Geoscience and Remote Sensing, vol. 99, pp. 1-13, 2020.

2019

M. Shahrimie Asaari, Mertens, S., Dhondt, S., Inze, D., Wuyts, N., and Scheunders, P., “Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform”, Computers and Electronics in Agriculture, vol. 162, pp. 749-758, 2019.
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.

2018

G. Liu, Nath, T., Guo, Z., Linneweber, G., Claeys, A., Li, J., Bengochea, M., De Backer, S., Weyn, B., Sneyders, M., Nicasy, H., Yu, P., Scheunders, P., and Hassan, B., “A simple computer vision pipeline reveals the effects of isolation on social interaction dynamics in Drosophila”, Plos Computational Biology, vol. 14, no. 8, p. e1006410, 2018.
B. Rasti, Scheunders, P., Ghesami, P., Licciardi, G., and Chanussot, J., “Noise reduction in hyperspectral imagery: overview and application”, Remote Sensing , vol. 10, no. 3, p. 482, 2018.
M. Shahrimie Asaari, Mishra, P., Mertens, S., Dhondt, S., Inze, D., Wuyts, N., and Scheunders, P., “Close-range hyperspectral image analysis for the early detection of plant stress responses in individual plants in a high-throughput phenotyping platform”, ISPRS Journal of Photogrammetry and Remote Sensing , vol. 138, pp. 121-138, 2018.

2017

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.
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.
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.
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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