Hybridization techniques for fast radiosity solvers

The authors study, both theoretically and experimentally some properties of classical linear systems solvers, according to the radiosity assumptions. We prove important properties for some of these solvers which allow the user to choose the best one. We then introduce a new technique, so called hybridization, whose purpose is to increase the convergence speed of iterative methods. It provides very efficient results for the well-known Gauss-Seidel solver. This technique has been successfully applied to both a group progressive radiosity approach and a full-matrix radiosity method which has been specifically designed for plant growth simulation.