Imaging Signal Recovery Using Neural Network Priors Under Uncertain Forward Model Parameters

arXiv:2405.02944v1 Announce Type: new
Abstract: Inverse imaging problems (IIPs) arise in various applications, with the main objective of reconstructing an image from its compressed measurements. This problem is often ill-posed for being under-determined with multiple interchangeably consistent solutions. The best solution inherently depends on prior knowledge or assumptions, such as the sparsity of the image. Furthermore, the reconstruction process for most IIPs relies significantly on the imaging (i.e. forward model) parameters, which might not be fully known, or the measurement …

abstract applications arxiv assumptions consistent cs.cv image imaging knowledge multiple network neural network parameters prior recovery signal solution solutions type uncertain