Browsing University of Waterloo by Supervisor "Xu, Linlin"
Now showing items 1-6 of 6
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Classification of Compact Polarimetric Synthetic Aperture Radar Images
(University of Waterloo, 2021-08-27)The RADARSAT Constellation Mission (RCM) was launched in June 2019. RCM, in addition to dual-polarization (DP) and fully quad-polarimetric (QP) imaging modes, provides compact polarimetric (CP) mode data. A CP synthetic ... -
Correction Methods for Non-Stationary Noise Floor in Sentinel-1 Images Using Convex Optimization
(University of Waterloo, 2020-09-03)Synthetic aperture radar (SAR) is a method of creating images of the surface of the Earth by emitting and receiving radar waves. Sentinel-1 is a SAR platform made by the European Space Agency (ESA) that provides a source ... -
Deep Image Prior for Disentangling Mixed Pixels
(University of Waterloo, 2022-08-19)A mixed pixel in remotely sensed images measures the reflectance and emission from multiple target types (e.g., tree, grass, and building) from a certain area. Mixed pixels exist commonly in spaceborne hyper-/multi-spectral ... -
Deep Learning Based Building Extraction from High-Resolution Remote Sensing Images
(University of Waterloo, 2022-07-11)Building extraction from remote sensing images is a critical task to support various applications such as cartography, disaster response, and urban planning. The automation of this task is an active research area due to ... -
Detection of Small Objects in UAV Images via an Improved Swin Transformer-based Model
(University of Waterloo, 2023-05-23)Automated detection of small objects such as vehicles in images of complex urban environments taken by unmanned aerial vehicles (UAV) is one of the most challenging tasks in computer vision and remote sensing communities, ... -
Mixture Regression for Sea Ice Segmentation
(University of Waterloo, 2022-12-23)The classification of sea ice in SAR imagery is complicated by statistical nonstationarity. Incidence angle effects, heterogeneous ice conditions and other confounding variables contribute to spatial and temporal variability ...