גיא גלבוע (הנדסת חשמל, טכניון)
יום שלישי, 12.11.2013, 11:30
חדר 337, בניין טאוב למדעי המחשב
new framework is proposed for variational analysis and processing. It defines a
functional-based nonlinear transform and inverse-transform. The framework is
developed in the context of total-variation (TV), but it can be generalized to other
An eigenfunction, with respect to the subdifferential of the functional, such as a
disk in the TV case, yields an impulse in the transform domain. This can be viewed
as a generalization of known spectral approaches, based on linear algebra, which
are extensively used in image-processing, e.g. for segmentation.
Following the Fourier intuition, a spectrum can be computed to analyze dominant
scales in the image. Moreover, new nonlinear low-pass, high-pass and band-pass
filters can be designed with very precise scale selection.
Relations to sparse signals and to nonlocal-TV will be discussed. An example of a
texture processing application will be shown, illustrating possible benefits of this