Remote Sensing

Remote Sensing is the research area in which the 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. Recently, research is shifted to more close-range applications, for which we have our own acquisition equipement (spectrometer 400-2500 nm; VNIR camera 400-900 nm and SWIR camera 1000-1700 nm). Applications are material characterization (corrosion, soil moisture, powder material composition).

Journal publications

2024

B. Koirala, Rasti, B., and Scheunders, P., “A Supervised Approach for Estimating Fractional Abundances of Binary Intimate Mixtures”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, pp. 1-11, 2024.PDF icon extensive_analysis_of_intimate_mixtures.pdf (4.49 MB)

2023

T. De Kerf, “Hyperspectral imaging for automated inspection of offshore wind infrastructure”, 2023.
K. Rafiezadeh Shahi, “Unsupervised machine/deep learning mapping (clustering) for single/multi-source remote sensing data ”, 2023.
B. Koirala, Rasti, B., Bnoulkacem, Z., Ribeiro, A. De Lima, Madriz, Y., Herrmann, E., Gestels, A., De Kerf, T., Lorenz, S., Fuchs, M., Janssens, K., Steenackers, G., Gloaguen, R., and Scheunders, P., “A Multisensor Hyperspectral Benchmark Dataset For Unmixing of Intimate Mixtures”, IEEE Sensors Journal, 2023.PDF icon a_multisensor_hyperspectral_benchmark_dataset_for_unmixing_of_intimate_mixtures_1_.pdf (22.13 MB)
B. Koirala, Mboga, N., Moelans, R., Knaeps, E., Sels, S., Winters, F., Samsonova, S., Vanlanduit, S., and Scheunders, P., “Study on the Potential of Oil Spill Monitoring in a Port Environment Using Optical Reflectance”, Remote Sensing, 2023.PDF icon remotesensing-15-04950_1.pdf (20.86 MB)

2022

B. Koirala, Zahiri, Z., and Scheunders, P., “A Robust Supervised Method for Estimating Soil Moisture Content From Spectral Reflectance”, IEEE Transactions on Geoscience and Remote Sensing , vol. 60, pp. 1-13, 2022.PDF icon soil_moisture_content.pdf (7.95 MB)
B. Rasti, Koirala, B., and Scheunders, P., “HapkeCNN: Blind Nonlinear Unmixing for Intimate Mixtures Using Hapke Model and Convolutional Neural Network”, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022.PDF icon nonlinear_unmixing.pdf (8.14 MB)
P. Ghosh, Roy, S. Kumar, Koirala, B., Rasti, B., and Scheunders, P., “Hyperspectral Unmixing Using Transformer Network”, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-16, 2022.PDF icon transformer_unmixing.pdf (6.32 MB)
M. Shahrimie Asaari, Mertens, S., Verbraeken, L., Dhondt, S., Inze, D. G., Koirala, B., and Scheunders, P., “Non-destructive analysis of plant physiological traits using hyperspectral imaging: A case study on drought stress”, Computers and Electronics in Agriculture, vol. 195, 2022.
B. Rast, Koirala, B., Scheunders, P., and Chanussot, J., “MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing”, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022.PDF icon ieee_journal_misicnet.pdf (11.02 MB)

Pages