Imaging through glass diffusers using densely connected convolutional networks

Understand

Computational imaging through scatter generally is accomplished by first characterizing the scattering medium so that its forward operator is obtained; and then imposing additional priors in the form of regularizers on the reconstruction functional so as to improve the condition of the originally ill-posed inverse problem.

• In the functional, the forward operator and regularizer must be entered explicitly or parametrically (e.g.
• scattering matrices and dictionaries, respectively.) However, the process of determining these representations is often incomplete, prone to errors, or infeasible.
• Recently, deep learning architectures have been proposed to instead learn both the forward operator and regularizer through examples.