R econstruction of given noisy data is an ill-posed problem and a computationally intensive task. Nonlinear regularization techniques are used to find a unique solution under certain constraints. In our contribution we present a parallel mixed-signal architecture which solves this nonlinear problem with in microseconds. By connecting all parallel cells in a circular manner it is possible to process noisy data vectors of infinite length. This is achieved by virtually shifting the nonlinear

more »

... ve filter kernel over the noisy data vector. Additionally, we focus on the interaction between theory, discretization, numerical simulations, macro-modeling, and analog VLSI implementation for a theoretically well understood class of computer vision in an exemplary and paradigmatic way. A one-dimensional (1D) experimental chip has been fabricated using 0.8 mm CMOS technology. On-chip measurements are shown to agree with results from numerical simulations. Results from applying the 1D chip to nonlinear smoothing of twodimensional image data will also be given correspondence.