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Remote sensing

Multispectral and hyperspectral satellite and aerial image processing and analysis

An Extensive Multisensor Hyperspectral Benchmark Datasets of Intimate Mixtures of Mineral Powders

B. Koirala, Rasti, B., Bnoulkacem, Z., Ribeiro, A. De Lima, Madriz, Y., Herrmann, E., Gestels, A., De Kerf, T., Janssens, K., Steenackers, G., Gloaguen, R., and Scheunders, P., “An Extensive Multisensor Hyperspectral Benchmark Datasets of Intimate Mixtures of Mineral Powders”, in IEEE International Geoscience and Remote Sensing Symposium, 2023, pp. 5890-5893.

Files:

igarss_2022_1.pdf

A Robust Supervised Method for Estimating Soil Moisture Content From Spectral Reflectance

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.

Files:

soil_moisture_content.pdf

Blind Nonlinear Unmixing For Intimate Mixtures Using Hapke Model And CNN

B. Rasti and Koirala, B., “Blind Nonlinear Unmixing For Intimate Mixtures Using Hapke Model And CNN”, in Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2022, pp. 1-5.

Files:

whispers_2022_hapkecnn.pdf

Hyperspectral Unmixing Using Transformer Network

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.

Files:

transformer_unmixing.pdf

A Robust Supervised Method to Estimate Chlorophyll Ab Content from Spectral Reflectance

B. Koirala and Scheunders, P., “A Robust Supervised Method to Estimate Chlorophyll Ab Content from Spectral Reflectance”, in IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 326-329.

Files:

igarss_2022.pdf

Deep Blind Unmixing using Minimum Simplex Convolutional Network

B. Rasti, Koirala, B., Scheunders, P., and Chanussot, J., “Deep Blind Unmixing using Minimum Simplex Convolutional Network”, in IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 28-31.

Files:

misicnet_igarss2022.pdf

SUnCNN: Sparse Unmixing Using Unsupervised Convolutional Neural Network

B. Rasti and Koirala, B., “SUnCNN: Sparse Unmixing Using Unsupervised Convolutional Neural Network”, IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2021.

Files:

ieee_grsl_sundip.pdf

BOOSTING HYPERSPECTRAL IMAGE UNMIXING USING DENOISING: FOUR SCENARIOS

B. Rasti, Koirala, B., Scheunders, P., Ghamisi, P., and Gloaguen, R., “BOOSTING HYPERSPECTRAL IMAGE UNMIXING USING DENOISING: FOUR SCENARIOS”, in IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021.

HapkeCNN: Blind nonlinear unmixing for intimate mixtures using Hapke model and convolutional neural network

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, 2022.

Files:

MS2A-Net: multi-view spectral-spatial association network for hyperspectral image clustering

K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Gloaguen, R., and Scheunders, P., “MS2A-Net: multi-view spectral-spatial association network for hyperspectral image clustering”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 6518-6530, 2022.

Files:

ms2a-net_multiscale_spectralspatial_association_network_for_hyperspectral_image_clustering.pdf

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