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20152021
most citedOptimising Spatial and Tonal Data for PDE-based Inpainting

18 citations · 20 across the 4 of their papers we have counts for

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Showing 2019Show all

10 papers · 1 filter

cs.CV2019

Variational Coupling Revisited: Simpler Models, Theoretical Connections, and Novel Applications

Aaron Wewior, Joachim Weickert

Variational models with coupling terms are becoming increasingly popular in image analysis. They involve auxiliary variables, such that their energy minimisation splits into multip…

eess.IV2019

Robustness of Brain Tumor Segmentation

Sabine Müller, Joachim Weickert, Norbert Graf

Purpose: The segmentation of brain tumors is one of the most active areas of medical image analysis. While current methods perform superhuman on benchmark data sets, their applicab…

eess.IV2019

Learning a Generic Adaptive Wavelet Shrinkage Function for Denoising

Tobias Alt, Joachim Weickert

The rise of machine learning in image processing has created a gap between trainable data-driven and classical model-driven approaches: While learning-based models often show super…

cs.CV2019

Object Segmentation Tracking from Generic Video Cues

Amirhossein Kardoost, Sabine Müller, Joachim Weickert +1

We propose a light-weight variational framework for online tracking of object segmentations in videos based on optical flow and image boundaries. While high-end computer vision met…

eess.IV2019

Poisson Noise Removal Using Multi-Frame 3D Block Matching

Kireeti Bodduna, Joachim Weickert

The 3D block matching (BM3D) filter belongs to the state-of-the-art techniques for eliminating additive white Gaussian noise from single-frame images. There exist four multi-frame…

eess.IV2019

Enhancing Patch-Based Methods with Inter-frame Connectivity for Denoising Multi-frame Images

Kireeti Bodduna, Joachim Weickert

The 3D block matching (BM3D) method is among the state-of-art methods for denoising images corrupted with additive white Gaussian noise. With the help of a novel inter-frame connec…