Image compression with anisotropic diffusion
Compression is an important field of digital image processing where well-engineered
methods with high performance exist. Partial differential equations (PDEs), however, have …
methods with high performance exist. Partial differential equations (PDEs), however, have …
Understanding, optimising, and extending data compression with anisotropic diffusion
Galić et al.(Journal of Mathematical Imaging and Vision 31: 255–269, 2008) have shown
that compression based on edge-enhancing anisotropic diffusion (EED) can outperform the …
that compression based on edge-enhancing anisotropic diffusion (EED) can outperform the …
Edge-based compression of cartoon-like images with homogeneous diffusion
Edges provide semantically important image features. In this paper a lossy compression
method for cartoon-like images is presented, which is based on edge information. Edges …
method for cartoon-like images is presented, which is based on edge information. Edges …
How to choose interpolation data in images
Z Belhachmi, D Bucur, B Burgeth, J Weickert - SIAM Journal on Applied …, 2009 - SIAM
We introduce and discuss shape-based models for finding the best interpolation data when
reconstructing missing regions in images by means of solving the Laplace equation. The …
reconstructing missing regions in images by means of solving the Laplace equation. The …
Unifying abstract inexact convergence theorems and block coordinate variable metric iPiano
P Ochs - SIAM Journal on Optimization, 2019 - SIAM
An abstract convergence theorem for a class of generalized descent methods that explicitly
models relative errors is proved. The convergence theorem generalizes and unifies several …
models relative errors is proved. The convergence theorem generalizes and unifies several …
Tensor field interpolation with PDEs
We present a unified framework for interpolation and regularisation of scalar-and tensor-
valued images. This framework is based on elliptic partial differential equations (PDEs) and …
valued images. This framework is based on elliptic partial differential equations (PDEs) and …
PDE-based Progressive Prediction Framework for Attribute Compression of 3D Point Clouds
X Yang, Y Shao, S Liu, TH Li, G Li - Proceedings of the 31st ACM …, 2023 - dl.acm.org
In recent years, the diffusion-based image compression scheme has achieved significant
success, which inspires us to use diffusion theory to employ the diffusion model for point …
success, which inspires us to use diffusion theory to employ the diffusion model for point …
Efficient data optimisation for harmonic inpainting with finite elements
V Chizhov, J Weickert - International Conference on Computer Analysis of …, 2021 - Springer
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 …
compression. We improve this approach in three important aspects. Firstly, we replace the …
Deep spatial and tonal data optimisation for homogeneous diffusion inpainting
Diffusion-based inpainting can reconstruct missing image areas with high quality from
sparse data, provided that their location and their values are well optimised. This is …
sparse data, provided that their location and their values are well optimised. This is …
Domain decomposition algorithms for real-time homogeneous diffusion inpainting in 4K
N Kämper, J Weickert - ICASSP 2022-2022 IEEE International …, 2022 - ieeexplore.ieee.org
Inpainting-based compression methods are qualitatively promising alternatives to transform-
based codecs, but they suffer from the high computational cost of the inpainting step. This …
based codecs, but they suffer from the high computational cost of the inpainting step. This …