基于像素合作博弈的非刚性图像配准方法

用离散位移场表示形变,将非刚性图像配准问题转化为马尔可夫随机场中的最大后验概率推理问题,从而等价于吉布斯随机场中的能量极小问题。为获得能量极小点,将配准视为像素间的博弈,提出了基于多人合作博弈的非刚性图像配准方法,设计了相应的确定性算法。博弈配准时,每个像素尝试与邻居结盟选择一致的位移向量,使自身和联盟的收益都最大化,迭代地完成配准。新方法能配准复杂的形变,精度高、鲁棒性好,非常适用于图像的精配准。实验结果验证了合作博弈配准方法的可行性和有效性。

Nonrigid image registration approach based on cooperative game among pixels

After representing the deformation as a field of discrete displacements, the nonrigid image registration problem can be considered as a maximum a posteriori inference problem in Markov random field, which can be optimized using pairwise Gibbs energy minimization technique. To find a minimum, the registration problem is modelled as a game among pixels, a novel approach for nonrigid image registration based on cooperative game theory is proposed, and a deterministic algorithm is designed. During the game, each pixel tries to form a coalition with its neighbors, and select a displacement to maximize the payoffs of itself and the coalition. Registration is achieved by an iterative process. The novel approach can register complicated deformation with high accuracy and good robustness, so it is very suitable for fine registration. Experimental results show that the cooperative game theoretic approach is feasible and effective.