Connections between Deep Equilibrium and Sparse Representation models with Application to Hyperspectral Imaging. (arXiv:2203.15901v2 [cs.CV] UPDATED)

Web: http://arxiv.org/abs/2203.15901

In this study, the problem of computing a sparse representation of
multi-dimensional visual data is considered. In general, such data e.g.,
hyperspectral images, color images or video data consists of signals that
exhibit strong local dependencies. A new computationally efficient sparse
coding optimization problem is derived by employing regularization terms that
are adapted to the properties of the signals of interest. Exploiting the merits
of the learnable regularization techniques, a neural network is employed to act
as structure prior and …

application arxiv cv deep equilibrium imaging models representation