Certainties and uncertainties in the principle of uncertainty
- University of Tel Aviv
Oct. 10, 2014, 2:30 p.m. - None
Measurement of features is a basic operation in signal/image processing (as well as in physics). The measure is done with the help of a "window” function which is localised around the measured feature(s). The principle of uncertainty limits the accuracy that one can achieve by jointly measuring two features. It also provides the window for which the inequality becomes an equality. We show in this work that one can design windows that provide better accuracy than the window given by the principle on uncertainty. We also show that this principle has an inherent ambiguity and that one should interpret it correctly in order to generalise this principle in a sensible way.
This is joint work with H-G Stark and R. Levie.
Nir Sochen is a professor of Applied Mathematics and Head of the School of Mathematical Sciences in Tel-Aviv University. He received his PhD in Theoretical Physics 1992 from Universite Paris-Sud while conducting his research in the Service de Physiqhe Theorique at the Centre d'Etude Nuclaire at Saclay. He did a postdoctoral research in Ecole Normale Superieure a Paris and at UC Berkeley. It is in the latter that his interests shifted towards the application of differential geometry and statistical mechanics ideas and techniques to Image Processing, Computer Vision and Medical Imaging.