We propose in this paper to unify two different ap-
proaches to image restoration: On the one hand, learning a
basis set (dictionary) adapted to sparse signal descriptions
has p...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
In this paper we study the impact of denoising the raw high angular resolution diffusion imaging (HARDI) data with the Non-Local Means filter adapted to Rician noise (NLMr). We fir...
Christian Barillot, Maxime Descoteaux, Nicolas Wie...
Obtaining high quality images in MR is desirable not only for accurate visual assessment but also for automatic processing to extract clinically relevant parameters. Filtering-bas...
Ganesh Adluru, Tolga Tasdizen, Ross Whitaker, Edwa...
State-of-the-art motion estimation algorithms suffer from three major problems: Poorly textured regions, occlusions and small scale image structures. Based on the Gestalt principle...
We claim and present arguments to the effect that a large class of manifold learning algorithms that are essentially local and can be framed as kernel learning algorithms will suf...