Comparative analysis of stochastic optimization algorithms for image registration

Abstract

This work is devoted to comparative experimental analysis of different stochastic optimization algorithms for image registration in spatial domain: stochastic gradient descent, Momentum, Nesterov momentum, Adagrad, RMSprop, Adam. Correlation coefficient is considered as the objective function. Experiments are performed on synthetic data generated via wave model with different noise-to-signal ratio.