The observed distribution of natural images is far from uniform. On the contrary, real images have complex and important structure that can be exploited for image processing, reco...
We propose a novel denoising algorithm to reduce the Poisson noise that is typically dominant in fluorescence microscopy data. To process large datasets at a low computational co...
Variational models for image segmentation have many applications, but can be slow to compute. Recently, globally convex segmentation models have been introduced which are very rel...
In this paper, we extend a (2-D) data-adaptive steering kernel regression framework for image processing to a (3-D) spatio-temporal framework for processing video. In particular, ...
This paper presents a new technique for noise removal in images. It benefits both from the recent advances in waveletbased and variational denoising. Whereas wavelet-based analys...