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eess.IV2025
Energy-based models for inverse imaging problems
Andreas Habring, Martin Holler, Thomas Pock +1
In this chapter we provide a thorough overview of the use of energy-based models (EBMs) in the context of inverse imaging problems. EBMs are probability distributions modeled via G…
eess.IV2025
Total Variation-Based Image Decomposition and Denoising for Microscopy Images
Marco Corrias, Giada Franceschi, Michele Riva +5
Experimentally acquired microscopy images are unavoidably affected by the presence of noise and other unwanted signals, which degrade their quality and might hide relevant features…
eess.IV2025
Bigger Isn't Always Better: Towards a General Prior for Medical Image Reconstruction
Lukas Glaszner, Martin Zach
Diffusion model have been successfully applied to many inverse problems, including MRI and CT reconstruction. Researchers typically re-purpose models originally designed for uncond…