Probabilistic Solution of Ill-Posed Problems in Computational Vision
Jose Luis Marroquin, Sanjoy K. Mitter, T. Poggio · Journal of the American Statistical Association · 1987
Computational vision is a set of inverse problems. We review standard regularization theory, discuss its limitations, and present new stochastic (in particular, Bayesian) methods for their solution. We derive efficient algorithms and describe parallel implementations on digital parallel SIMD architectures, as well as a new class of parallel hybrid computers.