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Aggelos K. Katsaggelos
Researcher at Northwestern University
Publications - 999
Citations - 28918
Aggelos K. Katsaggelos is an academic researcher from Northwestern University. The author has contributed to research in topics: Image restoration & Image processing. The author has an hindex of 76, co-authored 946 publications receiving 26196 citations. Previous affiliations of Aggelos K. Katsaggelos include University of Stavanger & Delft University of Technology.
Papers
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Proceedings ArticleDOI
Enhancement of low-dosage cine-angiographic image sequences using a modified expectation maximization algorithm
TL;DR: An approach to temporally filter x-ray image sequences acquired through fluoroscopy systems relies on a joint estimation of the signal and the displacement field through a maximum likelihood approach to facilitate a more tractable solution.
Journal ArticleDOI
An Adaptive Video Acquisition Scheme for Object Tracking and Its Performance Optimization
Srutarshi Banerjee,Henry H. Chopp,Juan G. Serra,Hao Tian Yang,Oliver Cossairt,Aggelos K. Katsaggelos +5 more
TL;DR: A novel adaptive host-chip modular architecture for video acquisition to optimize an overall objective task constrained under a given bit rate, which is modular and highly versatile in terms of flexibility in re-orienting the objective task.
Proceedings Article
Audio-visual anticipatory coarticulation modeling by human and machine.
TL;DR: A new statistical model of audio-visual speech, the asynchronydependent transition (ADT) model, is introduced, which allows asynchrony between audio and video states within word boundaries, where theaudio and video state transitions depend not only on the state of that modality, but also on the instantaneous as synchrony.
Proceedings Article
Image prior combination in super-resolution image reconstruction
TL;DR: A new combination of image priors is introduced and applied to Super Resolution (SR) image reconstruction by finding the distribution on the HR image given the observations that minimize a linear convex combination of the Kullback-Leibler (KL) divergences associated with each posterior distribution.
Proceedings ArticleDOI
Displacement field estimation using a coupled Gauss-Markov model
TL;DR: A model-based algorithm for obtaining the maximum a posteriori estimate of the displacement vector field (DVF) from two consecutive image frames of an image sequence with superior performance with respect to prediction error and robustness to occlusions is developed.