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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…
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…
Image Compression with Isotropic and Anisotropic Shepard Inpainting
Rahul Mohideen Kaja Mohideen, Tobias Alt, Pascal Peter +1
Inpainting-based codecs store sparse selected pixel data and decode by reconstructing the discarded image parts by inpainting. Successful codecs (coders and decoders) traditionally…
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…
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…
Regularised Diffusion-Shock Inpainting
Kristina Schaefer, Joachim Weickert
We introduce regularised diffusion--shock (RDS) inpainting as a modification of diffusion--shock inpainting from our SSVM 2023 conference paper. RDS inpainting combines two careful…