The Information Processing and Algorithms Laboratory (iPAL) is directed by Prof. Vishal Monga. Graduate research in iPAL broadly encompasses signal and image processing theory and applications with a particular focus on capturing practical real-world constraints via convex optimization theory and algorithms.
Estimating the disturbance or clutter covariance is a centrally important problem in radar space-time adpative processing (STAP) since since estimation of the disturbance or interference covariance matrix plays a central role on radar target detection in the presence of clutter, noise and a jammer.
Remote sensed imaging, such as synthetic aperture radar (SAR), infra-red (IR), hyperspectral etc. has seen vast improvements in the last decade due to advances in sensors and capture technology. Likewise, sophisticated image analysis and classification techniques may now be used to mine objects of interests in these images.
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