Associative Learning of Standard Regularizing Operators in Early Vision (opens in new tab)

Associative Learning of Standard Regularizing Operators in Early Vision Poggio, Tomaso; Hurlbert, Anya Standard regularization methods can be used to solve satisfactorily several problems in early vision, including edge detection, surface reconstruction, the computation of motion and the recovery of color. In this paper, we suggest (a) that quadratic variational principles corresponding to standard regularization methods are equivalent to a linear regularizing operator acting on the data and ...