21 citations · 54 across the 5 of their papers we have counts for
5 papers
An Efficient Approximate Method for Online Convolutional Dictionary Learning
Farshad G. Veshki, Sergiy A. Vorobyov
Most existing convolutional dictionary learning (CDL) algorithms are based on batch learning, where the dictionary filters and the convolutional sparse representations are optimize…
Convolutional Simultaneous Sparse Approximation with Applications to RGB-NIR Image Fusion
Farshad G. Veshki, Sergiy A. Vorobyov
Simultaneous sparse approximation (SSA) seeks to represent a set of dependent signals using sparse vectors with identical supports. The SSA model has been used in various signal an…
Efficient ADMM-based Algorithms for Convolutional Sparse Coding
Farshad G. Veshki, Sergiy A. Vorobyov
Convolutional sparse coding improves on the standard sparse approximation by incorporating a global shift-invariant model. The most efficient convolutional sparse coding methods ar…
Coupled Feature Learning for Multimodal Medical Image Fusion
Farshad G. Veshki, Nora Ouzir, Sergiy A. Vorobyov +1
Multimodal image fusion aims to combine relevant information from images acquired with different sensors. In medical imaging, fused images play an essential role in both standard a…
A Fast Dictionary Learning Method for Coupled Feature Space Learning
F. G. Veshki, S. A. Vorobyov
In this letter, we propose a novel computationally efficient coupled dictionary learning method that enforces pairwise correlation between the atoms of dictionaries learned to repr…