This paper describes a novel theoretical characterization of the performance of non-local means (NLM) for noise removal. NLM has proven effective in a variety of empirical studies, but little is understood fundamentally about how it performs relative to classical methods based on wavelets or how its parameters should be chosen. For cartoon images and images which may contain thin features and r...

High-Angle Annular Darkfield Scanning Transmission Electron Microscopy (HAADF-STEM) allows to take images at atomic scale with a contrast proportional to the atomic number. STEM acquires an image line-by-line, pixel-by-pixel leading to characteristic distortions. Furthermore, STEM images of beam sensitive materials have to be taken with short exposure times, leading to low contrast images with ...

Partial Differential equations (PDE), wavelets-based methods and neighborhood filters were proposed as locally adaptive machines for noise removal. Recently, Buades, Coll and Morel proposed the Non-Local (NL-) means filter for image denoising. This method replaces a noisy pixel by the weighted average of other image pixels with weights reflecting the similarity between local neighborhoods of th...

This paper proposes a novel method for document enhancement which combines two recent powerful noise-reduction steps. The first step is based on the total variation framework. It flattens background grey-levels and produces an intermediate image where background noise is considerably reduced. This image is used as a mask to produce an image with a cleaner background while keeping character deta...

Many important imaging problems in material science involve reconstruction of images containing repetitive non-local structures. Model-based iterative reconstruction (MBIR) could in principle exploit such redundancies through the selection of a log prior probability term. However, in practice, determining such a log prior term that accounts for the similarity between distant structures in the i...