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

2013

W. Liao, Pizurica, A., Scheunders, P., Philips, W., and Pi, Y., Semi-supervised local discriminant analysis for feature extraction in hyperspectral images, IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 1, pp. 184-198, 2013.
G. Thoonen, Spanhove, T., Vanden Borre, J., and Scheunders, P., Classification of heathland vegetation in a hierarchical contextual framework, International Journal of Remote Sensing, vol. 34, no. 1, pp. 96 - 111, 2013.

2012

Y. Zhang, Duijster, A., and Scheunders, P., A Bayesian Restoration Approach for Hyperspectral Images, IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 9, pp. 3453-3462, 2012.
G. Thoonen, Hufkens, K., Vanden Borre, J., Spanhove, T., and Scheunders, P., Accuracy assessment of contextual classification results for vegetation mapping, International Journal of Applied Earth Observation and Geoinformation, vol. 15, pp. 7 - 15, 2012.
G. Thoonen, Mahmood, Z., Peeters, S., and Scheunders, P., Multisource classification of color and hyperspectral images using color attribute profiles and composite decision fusion, Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, vol. 5, pp. 510 - 521, 2012.
G. Verdoolaege and Scheunders, P., On the geometry of Multivariate Generalized Gaussian models, Journal of Mathematical Imaging and Vision, vol. 43, no. 3, pp. 180-193, 2012.

2011

R. Heylen, Burazerovic, D., and Scheunders, P., Nonlinear spectral unmixing by geodesic simplex volume maximization, IEEE Journal of Selected Topics in Signal Processing, vol. 5, pp. 534-542, 2011.
R. Heylen, Burazerovic, D., and Scheunders, P., Fully constrained least-squares spectral unmixing by simplex projection, IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 11, pp. 4112-4122, 2011.PDF icon PDF (1.11 MB)Package icon Matlab code (1.93 KB)

Pages