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

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.

2010

2009

Y. Zhang, De Backer, S., and Scheunders, P., Noise-resistant wavelet-based Bayesian fusion of multispectral and hyperspectral images, IEEE Transactions on Geoscience and Remote Sensing, vol. 47, pp. 3834-3843, 2009.
A. Duijster, Scheunders, P., and De Backer, S., Wavelet-Based EM Algorithm for Multispectral-Image Restoration, IEEE Transactions on Geoscience and Remote Sensing, vol. 47, pp. 3892-3898, 2009.

2008

2007

Pages