Modeling representations of image patches that are quasi-invariant to spatial deformations is an important problem in computer vision. In this paper, we propose a novel concept, t...
Jan Ernst, Maneesh Kumar Singh, Visvanathan Ramesh
Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously wi...
In this paper, a new framework for brain warping via landmark matching is proposed using implicit representations or the level set method. We demonstrate this powerful technique b...
Alexia Leow, Paul M. Thompson, Hillary Protas, Sun...
Abstract. Most of the processing in vision today uses spatially invariant operations. This gives efficient and compact computing structures, with the conventional convenient separa...
by 0. In the discrete Fourier transform (DFT) domain, We propose a hybrid approach to wavelet-based image deconvolution that comprises Fourier-domain system inversion followed by w...
Ramesh Neelamani, Hyeokho Choi, Richard G. Baraniu...