Spatial Enhancement of Hyperspectral Satellite Imagery
Remote sensing technology has undeniable importance in various industrial applications. Some of which include mineral exploration, plant detection, defect detection in aerospace and shipbuilding, and optical gas imaging, to name a few. Remote sensing technology has been continuously evolving, offering a range of image types that can facilitate the aforementioned applications. One such type is Hyperspectral Images (HSIs). Unlike multispectral and natural images, HSIs consist of hundreds of bands, which makes it easier to identify objects through their spectral reflectance signals. Despite its high spectral resolution, HSIs suffer from low spatial resolution. This is a natural tradeoff that occurs due to cameras attempting to capture 3D images using 2D sensors. In order to implement remote sensing applications effectively with satisfying accuracy, HSIs need to have high spectral resolution as well as high spatial resolution. This webinar discusses the several advances in the field of HSI spatial enhancement, highlights and assesses the most recent state-of-the-art approaches, and draws the future direction of this research field.
Speaker
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Eng. Nour AburaedResearch Assistant @MBRSC Lab - University of DubaiNour Aburaed is a holder of BSc degree in Electrical and Computer Engineering and MSc degree in Electrical and Computer Engineering from Khalifa University of Science and Technology in Abu Dhabi – UAE. Her MSc is specialized in High-ISO Image De-noising and Quantum Image Processing. Nour was a Teaching Assistant for various math, physics, and programming courses at Khalifa University for two years. She has been working as a Research Assistant at Mohammed Bin Rashid Space Centre Laboratory based at the University of Dubai since 2018, where she specializes in applications of Image Processing and Artificial Intelligence within the context of remote sensing imagery. Nour is also currently a PhD student at the University of Strathclyde, where she studies the enhancement of Hyperspectral Satellite Imagery. Her research and study activities resulted in various publications in notable conferences and journals. Her current interests include object detection, semantic segmentation, single image super resolution, hyperspectral images, convolutional/complex/quantum neural networks, and data analytics and visualization.