Sparse representation in compressive sensing is gaining increasing attention due to its success in various applications. As we demonstrate in this paper, however, image sparse rep...
In this paper we propose an algorithm for image recovery where completely lost blocks in an image/video-frame are recovered using spatial information surrounding these blocks. Our...
Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously wi...
Multispectral scene information is useful for radiometric graphics, material identification and imaging systems simulation. The multispectral scene can be described as a datacube,...
We investigate the recovery of signals exhibiting a sparse representation in a general (i.e., possibly redundant or incomplete) dictionary that are corrupted by additive noise adm...
Christoph Studer, Patrick Kuppinger, Graeme Pope, ...