most citedOn Tensor-Based PDEs and their Corresponding Variational Formulations with Application to Color Image Denoising

13 citations · 30 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20267 cited

A Tensor Variational Formulation of Gradient Energy Total Variation

Freddie Åström, George Baravdish, Michael Felsberg

We present a novel variational approach to a tensor-based total variation formulation which is called gradient energy total variation, GETV. We introduce the gradient energy tensor…

cs.CV20263 cited

Mapping-Based Image Diffusion

Freddie Åström, Michael Felsberg, George Baravdish

In this work, we introduce a novel tensor-based functional for targeted image enhancement and denoising. Via explicit regularization, our formulation incorporates application depen…

cs.CV20262 cited

On the Choice of Tensor Estimation for Corner Detection, Optical Flow and Denoising

Freddie Åström, Michael Felsberg

Many image processing methods such as corner detection, optical flow and iterative enhancement make use of image tensors. Generally, these tensors are estimated using the structure…

cs.CV202613 cited

On Tensor-Based PDEs and their Corresponding Variational Formulations with Application to Color Image Denoising

Freddie Åström, George Baravdish, Michael Felsberg

The case when a partial differential equation (PDE) can be considered as an Euler-Lagrange (E-L) equation of an energy functional, consisting of a data term and a smoothness term i…

cs.CV20265 cited

Targeted Iterative Filtering

Freddie Åström, Michael Felsberg, George Baravdish +1

The assessment of image denoising results depends on the respective application area, i.e. image compression, still-image acquisition, and medical images require entirely different…