Diffusion posterior sampling for general noisy inverse problems
Diffusion models have been recently studied as powerful generative inverse problem
solvers, owing to their high quality reconstructions and the ease of combining existing …
solvers, owing to their high quality reconstructions and the ease of combining existing …
Plug-and-play methods for integrating physical and learned models in computational imaging: Theory, algorithms, and applications
Plug-and-play (PnP) priors constitute one of the most widely used frameworks for solving
computational imaging problems through the integration of physical models and learned …
computational imaging problems through the integration of physical models and learned …
Direct diffusion bridge using data consistency for inverse problems
Diffusion model-based inverse problem solvers have shown impressive performance, but
are limited in speed, mostly as they require reverse diffusion sampling starting from noise …
are limited in speed, mostly as they require reverse diffusion sampling starting from noise …
Prompt-tuning latent diffusion models for inverse problems
We propose a new method for solving imaging inverse problems using text-to-image latent
diffusion models as general priors. Existing methods using latent diffusion models for …
diffusion models as general priors. Existing methods using latent diffusion models for …
What's in a Prior? Learned Proximal Networks for Inverse Problems
Proximal operators are ubiquitous in inverse problems, commonly appearing as part of
algorithmic strategies to regularize problems that are otherwise ill-posed. Modern deep …
algorithmic strategies to regularize problems that are otherwise ill-posed. Modern deep …
Video Super-Resolution Using Plug-and-Play Priors
MC Zerva, LP Kondi - IEEE Access, 2024 - ieeexplore.ieee.org
Video super-resolution is a fundamental task in computer vision, aiming to enhance the
resolution and visual quality of low-resolution videos. Plug-and-Play Priors is one of the …
resolution and visual quality of low-resolution videos. Plug-and-Play Priors is one of the …
Efficient compressed sensing reconstruction for 3D fluorescence microscopy using OptoMechanical Modulation Tomography (OMMT) with a 1+ 2D regularization
OptoMechanical Modulation Tomography (OMMT) exploits compressed sensing to
reconstruct high resolution microscopy volumes from fewer measurement images compared …
reconstruct high resolution microscopy volumes from fewer measurement images compared …
[HTML][HTML] Using an Improved Regularization Method and Rigid Transformation for Super-Resolution Applied to MRI Data
Super-resolution (SR) techniques have shown significant promise in enhancing the
resolution of MRI images, which are often limited by hardware constraints and acquisition …
resolution of MRI images, which are often limited by hardware constraints and acquisition …
Trinidi: Time-of-flight resonance imaging with neutrons for isotopic density inference
Accurate reconstruction of 2D and 3D isotope densities is a desired capability with great
potential impact in applications such as evaluation and development of next-generation …
potential impact in applications such as evaluation and development of next-generation …
Closed-Form Approximation of the Total Variation Proximal Operator
Total variation (TV) is a widely used function for regularizing imaging inverse problems that
is particularly appropriate for images whose underlying structure is piecewise constant. TV …
is particularly appropriate for images whose underlying structure is piecewise constant. TV …