An Extended Krylov Subspace Method for Decoding Edge‐Based Compressed Images by Homogeneous Diffusion

The heat equation is often used to inpaint dropped data in inpainting-based lossy compression schemes. We propose an alternative way to numerically solve the heat equation by an extended Krylov subspace method. The method is very efficient with respect to the computation of the solution of the heat equation at large times. And this is exactly what is needed for decoding edge-compressed pictures by homogeneous diffusion.

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Publication Details

Journal
Repository KITopen (Karlsruhe Institute of Technology)
Published
2026-01-01
DOI
https://doi.org/10.5445/ir/1000189324
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
Field-Weighted Citation Impact
0.00
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article

An Extended Krylov Subspace Method for Decoding Edge‐Based Compressed Images by Homogeneous Diffusion

Volker Grimm, Kevin Liang
Repository KITopen (Karlsruhe Institute of Technology)
Generative Adversarial Networks and Image Synthesis
article

An Extended Krylov Subspace Method for Decoding Edge‐Based Compressed Images by Homogeneous Diffusion

Volker Grimm, Kevin Liang
article en

Abstract

The heat equation is often used to inpaint dropped data in inpainting-based lossy compression schemes. We propose an alternative way to numerically solve the heat equation by an extended Krylov subspace method. The method is very efficient with respect to the computation of the solution of the heat equation at large times. And this is exactly what is needed for decoding edge-compressed pictures by homogeneous diffusion.

Repository KITopen (Karlsruhe Institute of Technology)
Openalex Percentile: Top 97%
Generative Adversarial Networks and Image Synthesis
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An Extended Krylov Subspace Method for Decoding Edge‐Based Compressed Images by Homogeneous Diffusion — Volker Grimm, Kevin Liang · Repository KITopen (Karlsruhe Institute of Technology) (2026) | TGRS Research Map | TGRS