April 23, Tuesday
12:00 – 13:00
Detection of Faint Edges in Noisy Images: Statistical Limits, Computational Efficiency and their Interplay
Computer Science seminar
Lecturer : Boaz Nadler
Affiliation : Department of Computer Science and Applied Mathematics , Weizmann Institute of Science
Location : 202/37
Host : Dr. Aryeh Kontorovich
Detection of edges in images is a fundamental task in low level image
processing.
Edges are important as they mark the locations of discontinuities in
depth, surface orientation, or reflectance. Their detection can
facilitate a variety of tasks including image segmentation and object
recognition, with many applications ranging from medical to security.
In this talk we focus on accurate detection of faint, low-contrast
edges in very noisy images.
This challenging problem raises some fundamental statistical and
computational questions, for which we shall provide some (partial)
answers:
What are detection limits and how do these depend on the complexity of
the assumed edges ?
What are computationally efficient methods to detect various families
of edges ?
and finally, how well can one detect edges under severe computational
constraints - namely with sub-linear complexity in the number of image
pixels.
Joint work with Inbal Horev, Sharon Alpert, Meirav Galun, Ronen Basri
(WIS) and with Ery Arias-Castro (UCSD).