@conference {12435,
	title = {Blurring-invariant Riemannian metrics for comparing signals and images},
	booktitle = {2011 IEEE International Conference on Computer Vision (ICCV)},
	year = {2011},
	month = {2011/11/06/13},
	pages = {1770 - 1775},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We propose a novel Riemannian framework for comparing signals and images in a manner that is invariant to their levels of blur. This framework uses a log-Fourier representation of signals/images in which the set of all possible Gaussian blurs of a signal, i.e. its orbits under semigroup action of Gaussian blur functions, is a straight line. Using a set of Riemannian metrics under which the group actions are by isometries, the orbits are compared via distances between orbits. We demonstrate this framework using a number of experimental results involving 1D signals and 2D images.},
	keywords = {blurring-invariant Riemannian metrics, Estimation, Fourier transforms, Gaussian blur function, Gaussian processes, image representation, log-Fourier representation, measurement, Orbits, Polynomials, signal representation, Space vehicles, vectors},
	isbn = {978-1-4577-1101-5},
	doi = {10.1109/ICCV.2011.6126442},
	author = {Zhengwu Zhang and Klassen, E. and Srivastava, A. and Turaga,P. and Chellapa, Rama}
}
