activity
20212026
collaborators

6 papers

eess.IV2026

Optimising Inpainting Data with Delaunay Averages

Vassillen Chizhov, Joachim Weickert

Inpainting-based image compression usually stores an optimised subset of all pixel locations and their colour values. In the decoding phase, the missing data are approximated via i…

eess.IV2026

Optimizing Multiple Feature Types for Image Inpainting in the Linear and Nonlinear Setting

Vassillen Chizhov, Ferdinand Jost, Joachim Weickert

Inpainting-based compression stores a carefully optimized subset of the full image data and reconstructs the missing data by inpainting. The quality of these lossy codecs depends d…

eess.IV2024

Efficient Parallel Algorithms for Inpainting-Based Representations of 4K Images -- Part I: Homogeneous Diffusion Inpainting

Niklas Kämper, Vassillen Chizhov, Joachim Weickert

In recent years inpainting-based compression methods have been shown to be a viable alternative to classical codecs such as JPEG and JPEG2000. Unlike transform-based codecs, which…

eess.IV2024

Efficient Parallel Data Optimization for Homogeneous Diffusion Inpainting of 4K Images

Niklas Kämper, Vassillen Chizhov, Joachim Weickert

Homogeneous diffusion inpainting can reconstruct missing image areas with high quality from a sparse subset of known pixels, provided that their location as well as their gray or c…

eess.IV2023

Connecting Image Inpainting with Denoising in the Homogeneous Diffusion Setting

Daniel Gaa, Vassillen Chizhov, Pascal Peter +2

While local methods for image denoising and inpainting may use similar concepts, their connections have hardly been investigated so far. The goal of this work is to establish links…

eess.IV2021

Efficient Data Optimisation for Harmonic Inpainting with Finite Elements

Vassillen Chizhov, Joachim Weickert

Harmonic inpainting with optimised data is very popular for inpainting-based image compression. We improve this approach in three important aspects. Firstly, we replace the standar…