Inpainting, the technique of modifying an image in an undetectable form, is as ancient as art
itself. The goals and applications of inpainting are numerous, from the restoration of …

Techniques from sparse signal representation are beginning to see significant impact in
computer vision, often on nontraditional applications where the goal is not just to obtain a …

Relations between anisotropic diffusion and robust statistics are described in this paper.
Specifically, we show that anisotropic diffusion can be seen as a robust estimation procedure …

Sparse coding---that is, modelling data vectors as sparse linear combinations of basis
elements---is widely used in machine learning, neuroscience, signal processing, and statistics. …

We propose in this paper to unify two different approaches to image restoration: On the one
hand, learning a basis set (dictionary) adapted to sparse signal descriptions has proven to …

A novel scheme for the detection of object boundaries is presented. The technique is based
on active contours evolving in time according to intrinsic geometric measures of the image. …

Sparse coding—that is, modelling data vectors as sparse linear combinations of basis
elements—is widely used in machine learning, neuroscience, signal processing, and statistics. …

This book provides an introduction to the use of geometric partial differential equations in
image processing and computer vision. This research area brings a number of new concepts …

LOCO-I (LOw COmplexity LOssless COmpression for Images) is the algorithm at the core of
the new ISO/ITU standard for lossless and near-lossless compression of continuous-tone …

Sparse representations of signals have drawn considerable interest in recent years. The
assumption that natural signals, such as images, admit a sparse decomposition over a …