Department of Electrical & Computer Engineering, University of Manitoba

“Sparsity-based image processing”

Date: Thursday, October 18, 2018

I will give a brief tutorial on sparse representation of signals and images using over-complete dictionaries. I will then discuss deterministic and Bayesian sparsity-based methods for image restoration and denoising. Finally, I will present new results on unsupervised spectral unmixing of hyperspectral imaging data using our recently developed multi-channel least angle regression algorithm, a new sparsity-based method.

Bio: Dr. Sherif is an Associate Professor in the Electrical & Computer Engineering Department and is a core faculty member of the Graduate Biomedical Engineering Program at The University of Manitoba. His research interests include Digital Image Processing (M.Sc., University of Wisconsin-Madison) and Optics (Ph.D., University of Colorado at Boulder). Before arriving at the University of Manitoba, he held research positions at The University of Oxford, Imperial College London and National Research Council of Canada. He was also a Lecturer in Applied Optics (assistant professor) at the University of Kent, UK. He is author or co-author of over 100 scientific publications, including four patents.

Important Date

February 18 – February 22: Reading Week (No classes)

Upcoming Exam

STAT 1000 Midterm
Monday, March 4 at 5:30 p.m.

Upcoming Seminars

Statistics seminar: Aleeza Gerstein: “Levelling up R for Statistical Research and Teaching (Vignettes from RStudio::Conf)” — Thursday, February 28 at 2:45 p.m., P230 Duff Roblin.

Statistics seminar: Jame Fu: “Distribution of number of Levels in [s]-specified random permutation: A finite Markov Chain Imbedding Approach” — Thursday, March 7 at 2:45 p.m., P230 Duff Roblin.

Statistics seminar: Alison Gibbs: “Teaching Statistics in a Data Science World” — Thursday, March 21 at 2:45 p.m., P230 Duff Roblin.

Where are they now?

Llwellyn Maria Armstrong, M.Sc (1992)

Julie Mojica, M.Sc. (2003)