Algorithms based on the minimization of the Total Variation are prevalent in computer vision. They are used in a variety of applications such as image denoising, compressive sensi...
In fluorescence microscopy the noise level and the photobleaching are cross-dependent problems since reducing exposure time to reduce photobleaching degrades image quality while ...
Marcio de Moraes Marim, Elsa D. Angelini, Jean-Chr...
Sparse Orthonormal Transforms (SOT) has recently been proposed as a data compression method that can achieve sparser representations in transform domain. Given initial conditions,...
In this paper, we propose a new and powerful shape denoising technique for processing surfaces approximated by triangle meshes and soups. Our approach is inspired by recent non-lo...
Shin Yoshizawa, Alexander G. Belyaev, Hans-Peter S...
This paper introduces a novel stochastic approach to image denoising using an adaptive Monte Carlo scheme. Random samples are generated from the image field using a spatially-adap...
Alexander Wong, Akshaya Kumar Mishra, Paul W. Fieg...