This paper examines the relationship between wavelet-based image processing algorithms and variational problems. Algorithms are derived as exact or approximate minimizers of varia...
Antonin Chambolle, Ronald A. DeVore, Nam-Yong Lee,...
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
The symbol error probability (SEP) performance of time-hopping (TH) ultra-wideband (UWB) systems in the presence of multiuser interference (MUI) and timing jitter is considered wit...
N. V. Kokkalis, P. Takis Mathiopoulos, George K. K...
A variational Bayesian framework is employed in the paper for image segmentation using color clustering. A Gaussian mixture model is used to represent color distributions. Variati...
In this paper we extend a form of kernel ridge regression for data characterised by a heteroscedastic noise process (introduced in Foxall et al. [1]) in order to provide approxima...
Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Fo...