128 citations · 155 across the 10 of their papers we have counts for
12 papers · 1 filter
Unsupervised Single Image Dehazing Using Dark Channel Prior Loss
Alona Golts, Daniel Freedman, Michael Elad
Single image dehazing is a critical stage in many modern-day autonomous vision applications. Early prior-based methods often involved a time-consuming minimization of a hand-crafte…
A Local Block Coordinate Descent Algorithm for the Convolutional Sparse Coding Model
Ev Zisselman, Jeremias Sulam, Michael Elad
The Convolutional Sparse Coding (CSC) model has recently gained considerable traction in the signal and image processing communities. By providing a global, yet tractable, model th…
Unified Single-Image and Video Super-Resolution via Denoising Algorithms
Alon Brifman, Yaniv Romano, Michael Elad
Single Image Super-Resolution (SISR) aims to recover a high-resolution image from a given low-resolution version of it. Video Super Resolution (VSR) targets series of given images,…
Variations on the CSC model
Ives Rey-Otero, Jeremias Sulam, Michael Elad
Over the past decade, the celebrated sparse representation model has achieved impressive results in various signal and image processing tasks. A convolutional version of this model…
Finding GEMS: Multi-Scale Dictionaries for High-Dimensional Graph Signals
Yael Yankelevsky, Michael Elad
Modern data introduces new challenges to classic signal processing approaches, leading to a growing interest in the field of graph signal processing. A powerful and well establishe…
MMSE Approximation For Sparse Coding Algorithms Using Stochastic Resonance
Dror Simon, Jeremias Sulam, Yaniv Romano +2
Sparse coding refers to the pursuit of the sparsest representation of a signal in a typically overcomplete dictionary. From a Bayesian perspective, sparse coding provides a Maximum…