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).
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Journal publications
2018
“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. ,
“Noise reduction in hyperspectral imagery: overview and application”, Remote Sensing , vol. 10, no. 3, p. 482, 2018. ,
“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
“Evaluating palmiet wetland decline: a comparison of three methods”, Remote Sensing Applications: Society and Environment, vol. 8, pp. 212-223, 2017. ,
“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. ,
“Spatial Resolution Enhancement of Hyperspectral Images Using Spectral Unmixing and Bayesian Sparse Representation”, Remote Sensing, vol. 9, no. 6, 2017. ,
“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. ,
“Habitat mapping and quality assessment of NATURA 2000 Heatland using airborne imaging spectroscopy”, Remote Sensing, vol. 9, no. 3, 2017. ,
“Hyperspectral leaf reflectance of Carpines betulus L. saplings for urban air quality estimation”, Environmental Pollution, vol. 220, pp. 159-167, 2017. ,
“Estimation of the number of endmembers in a hyperspectral image via the hubness phenomenon”, IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 4, pp. 2191-2200, 2017. ,