An artificial immune network genetic algorithm for BRDF parameter inversion

The optimization parameters of bidirectional reflectance distribution function (BRDF) five parameters statistical model has been obtained by artificial immune network genetic algorithm (AINGA). A comparison of the genetic simulated annealing algorithm (GSAA) and the AINGA were presented. Both GSAA and AINGA were used to fit multi-angle experiment data to the BRDF statistical model. The differences between these two optimization algorithms in the computational accuracy, calculation duration, data fitting, RMS and parameters inversion results were compared and analyzed. Numerical results showed that using AINGA and GSAA has almost the same computational accuracy. But the AINGA has the obvious advantages in computing efficiency. Therefore, this optimization algorithm has the wide prospects of the application in the analysis of BRDF parameter inversion.