中文摘要：

针对现有的融合方法不能根据融合图像的后续使用目的对融合规则进行调整的问题,提出一个基于数据同化和遗传退火算法的多聚焦图像融合框架.该框架将小波变换作为模型算子,把主成分分析法作为观测算子,根据后续处理对图像各个属性指标值的依赖程度确定各个属性指标的权重;再用各个评价指标的加权和来构造目标函数;利用遗传退火算法优化目标函数,以获取更合适的图像.最后通过一组实验证明了该框架的有效性.

英文摘要：

The existing image fusion methods usually set down the fusion rules before fusion processes. However, the rules which determine the attributes of fusion results could not be adjusted according to different future applications. In order to overcome this limitation, a framework for multi- focus image fusion is proposed based on data assimilation and genetic annealing algorithm. Under this framework, the wavelet transition method is regarded as the model operator, while the principal component analysis method is considered as the observation operator. The weights of different attributes are determined according to their different importance to the post-processing. The weighted sum of the evaluation indices is used to construct the object function. Finally, the object function is optimized by using genetic annealing to obtain the proper image. The experiments validate the effectiveness of the framework.