  We propose a novel genetic algorithm to solve the image deformation
estimation problem by preserving the genetic diversity. As a classical problem,
there is always a trade-off between the complexity of deformation models and
the difficulty of parameters search in image deformation. 2D cubic B-spline
surface is a highly free-form deformation model and is able to handle complex
deformations such as fluid image distortions. However, it is challenging to
estimate an apposite global solution. To tackle this problem, we develop a
genetic operation named probabilistic bitwise operation (PBO) to replace the
crossover and mutation operations, which can preserve the diversity during
generation iteration and achieve better coverage ratio of the solution space.
Furthermore, a selection strategy named annealing selection is proposed to
control the convergence. Qualitative and quantitative results on synthetic data
show the effectiveness of our method.
